WO2015190136A1 - 画像処理システム及びコンピュータ読み取り可能な記録媒体 - Google Patents
画像処理システム及びコンピュータ読み取り可能な記録媒体 Download PDFInfo
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Definitions
- the present invention relates to an image processing system and a computer readable recording medium.
- Patent Document 1 JP-A-2012-168936
- an image processing system may include a luminance evaluation value deriving unit that derives an evaluation value of the luminance of at least a partial region of the image.
- the image processing system may include a saturation evaluation value deriving unit that derives an evaluation value of saturation of at least a partial area of an image.
- the image processing system may include a contrast evaluation value deriving unit that derives an evaluation value of the contrast of at least a part of the image.
- the image processing system may include a haze concentration estimation unit that derives an estimated value of haze concentration of the image based on the evaluation value of the brightness, the evaluation value of the saturation, and the evaluation value of the contrast.
- the image processing system may include a first pixel extraction unit that extracts pixels that are neither flat nor strong edge from the image, and the haze concentration estimation unit may be the flat or strong pixels extracted by the first pixel extraction unit.
- the estimated value of the haze concentration may be derived based on the evaluation value of the luminance of the pixel that is not an edge, the evaluation value of the saturation, and the evaluation value of the contrast.
- an image processing system may include a first pixel extraction unit that extracts pixels having neither flat nor strong edges from the image.
- the image processing system may further include the evaluation value of luminance of a pixel having neither flat nor strong edge, the evaluation value of saturation, and the evaluation value of contrast, which are extracted by the first pixel extraction unit.
- a haze concentration estimation unit may be provided to derive an estimated value of haze concentration of an image.
- the evaluation value of the luminance may be an average luminance value of the area.
- the evaluation value of the saturation may be an average saturation value of the area.
- the evaluation value of the contrast may be the contrast value of the area.
- the haze concentration estimation unit may derive an estimated value of the haze concentration that has a higher value as the average luminance value is higher.
- the haze concentration estimation unit may derive an estimated value of the haze concentration that has a higher value as the average saturation value is lower.
- the haze density estimation unit may derive an estimated value of the haze density that has a higher value as the contrast value is lower.
- the image may be a moving image including a plurality of frames, and the image processing system extracts a high saturation pixel for extracting a high saturation pixel whose saturation is higher than a predetermined threshold value in one of the plurality of frames. Different criteria depending on whether the high saturation pixel ratio is higher than a predetermined threshold or not, and a high saturation pixel ratio deriving unit that derives a high saturation pixel ratio indicating the ratio of the high saturation pixels in the one frame;
- the image processing apparatus may further include a scene change determination unit that determines whether the image includes a scene change.
- the image processing system derives the reliability of deriving the reliability of the estimated value of the haze concentration of the one frame based on the high saturation pixel rate of the one frame and the average luminance value of the one frame. You may have a department.
- the image processing system is based on the reliability of the estimated value of the haze density of the one frame derived by the reliability deriving unit and a scene change flag indicating whether the one frame is a scene-changed frame.
- the image processing apparatus may further include a parameter adjustment unit that adjusts a parameter used for the haze removal process for the one frame.
- the image processing system performs a haze removal process on the image based on a transmittance deriving unit that derives a transmittance corresponding to the haze concentration for each of a plurality of pixels of the image, and the estimated value of the haze concentration and the transmittance. And a haze removing unit to perform.
- the image processing system may further include a second pixel extraction unit for extracting pixels that are neither flat nor strong edge from the image, and the haze removal unit may be the flat or strong even extracted by the second pixel extraction unit. Whether the haze removal process is to be performed may be determined based on the proportion of pixels that are not edges in the image.
- an image processing system may include a high saturation pixel extraction unit which extracts high saturation pixels whose saturation is higher than a predetermined threshold value from one of a plurality of frames included in a moving image.
- the image processing system may include a high saturation pixel rate deriving unit that derives a high saturation pixel rate indicating the proportion of the high saturation pixels in the one frame.
- the image processing system determines whether a scene change is included in the image based on different criteria depending on whether the high saturation pixel rate in the one frame is higher than a predetermined threshold.
- a scene change determination unit may be provided.
- the scene change determination unit includes the scene change in the image based on the hue of the one frame and the hue of the past frame of the one frame when the high saturation pixel rate is higher than the threshold. It may be determined whether or not.
- the scene change determination unit performs scene change on the image based on the high chroma pixel rate of the one frame and the high chroma pixel rate of the previous frame of the one frame. May be determined.
- the image processing system is based on a haze density estimated value acquiring unit for acquiring an estimated value of haze density of the one frame, the high saturation pixel rate in the one frame, and an average luminance value of the one frame And a reliability deriving unit that derives the reliability of the estimated value of the haze concentration.
- the reliability deriving unit derives higher reliability as the average luminance value is larger, and derives higher reliability as the high saturation pixel rate is lower.
- the estimated value is equal to or less than a predetermined threshold value
- the reliability deriving unit derives higher reliability as the average luminance value is smaller, and derives higher reliability as the high saturation pixel rate is higher. Good.
- the image processing system includes a target value acquisition unit for acquiring a haze concentration target value, and a past frame of the one frame acquired by the target value acquisition unit based on the reliability calculated by the reliability calculation unit. And a target value determination unit that determines which of the haze concentration target value of and the estimated value of the haze concentration acquired by the haze concentration estimated value acquisition unit to use for adjusting the parameter used for the haze removal processing You may
- the image processing system includes a difference absolute value deriving unit that derives a difference absolute value between the haze concentration target value acquired by the target value acquisition unit and the estimated value of the haze concentration acquired by the haze concentration estimated value acquisition unit.
- the target value determination unit may obtain the target value based on the reliability of the estimated value and the difference absolute value, or a scene change flag indicating whether the one frame is a scene-changed frame. It may be determined which one of the haze concentration target value acquired by the part and the estimated value of the haze concentration acquired by the haze concentration estimated value acquisition part to use for adjusting the parameter used for the haze removal processing.
- the image processing system causes the parameter used for the haze removal processing of the one frame to gradually approach the target haze concentration value determined by the target value determination unit or the value corresponding to the estimated value of the haze concentration.
- a parameter adjustment unit may be provided to adjust the The parameter adjustment unit is a difference absolute value between the haze concentration target value determined by the target value determination unit or the estimated value of the haze concentration, and the parameter used for the haze removal processing of the past frame of the one frame
- the target value determining unit is a parameter used for the haze removal processing, with an adjustment amount according to the reliability of the estimated value of the haze density and a scene change flag indicating whether the one frame is a scene-changed frame It may adjust so that it may be approached in steps to the value corresponding to the above-mentioned target value of haze concentration determined by or the estimated value of the above-mentioned haze concentration.
- an image processing system may include a haze density acquisition unit that acquires the haze density of the image.
- the image processing system may include a removal processing unit that performs haze removal processing with different degrees of haze removal on the reflectance component of the image and the illumination light component of the image based on the haze concentration.
- the image processing system may include a combining unit configured to combine the reflectance component and the illumination light component subjected to the haze removal processing.
- the removal processing unit can approximate that there is no reflectance component contained in atmospheric light, the reflectance component of the image and the illumination light component of the image using the atmospheric model of the haze image and the Retinex theory And, the haze removal processing in which the haze removal degree differs, respectively may be given.
- the removal processing unit further assumes that the atmospheric model of the haze image can be applied only to the illumination light component, using the atmospheric model of the haze image and the Retinex theory, and the reflectance component of the image and the above
- the illumination light component of the image may be subjected to haze removal processing with different degrees of haze removal.
- a computer readable recording medium having recorded thereon a program for causing a computer to function as the image processing system.
- FIG. 1 schematically shows an example of a functional configuration of an image processing system 100.
- concentration estimation part 200 is shown roughly. It is a figure for demonstrating the extraction process of a flat & strong edge pixel.
- An example of the weighting graph 240 is schematically shown.
- An example of the weighting graph 242 is schematically shown. It is a figure for demonstrating a histogram value.
- An example of a function structure of the scene control part 300 is shown roughly.
- An example of a function structure of the scene change determination part 310 is shown roughly.
- An example of a function structure of the haze reliability estimation part 330 is shown roughly.
- An example of weighting graph 352 is shown roughly.
- An example of weighting graph 354 is shown roughly.
- An example of a function structure of the haze removal parameter adjustment part 360 is shown roughly.
- An example of a function structure of the haze removal part 400 is shown roughly.
- FIG. 1 schematically illustrates an example of a functional configuration of an image processing system 100.
- the image processing system 100 may be a display device that removes and displays the haze included in the input image.
- the haze includes general atmospheric phenomena in which the visibility is deteriorated by the fine particles.
- haze includes fog, haze, smoke, smoke, dust, dust, rain, snow and the like.
- the display device may be a liquid crystal display, a plasma display, an organic EL display, or the like.
- the image processing system 100 includes an image input unit 110, a display unit 120, a haze concentration estimation unit 200, a scene control unit 300, and a haze removal unit 400.
- the image input unit 110 inputs an image.
- the image may be a moving image or a still image, or may be a frame included in the moving image.
- the image input unit 110 may input RGB data, YUV data or HSV data.
- the image processing system 100 may convert the input YUV data into RGB data.
- the haze concentration estimation unit 200 derives an estimated value of the haze concentration for each input image.
- the haze density of an image is the density of haze contained in an image. For example, when the same space is imaged, the haze density of the image is higher when the density of the space fog is high than when the density of the space fog is low.
- the scene control unit 300 determines whether the input moving image includes a scene change.
- the scene control unit 300 may generate a parameter used for the haze removal processing based on whether or not a scene change is included in the input moving image.
- the haze removing unit 400 removes the haze from the input image.
- the haze removing unit 400 may remove the haze from the input image using the parameters generated by the scene control unit 300.
- the display unit 120 displays the image from which the haze has been removed by the haze removing unit 400.
- the scene control unit 300 when a scene change is not detected in a moving image, the scene control unit 300 generates a parameter used for the haze removal process in order to change the haze removal intensity stepwise over a plurality of frames. Then, by using the parameters generated by the scene control unit 300, the haze removal unit 400 changes the intensity of haze removal stepwise over a plurality of frames when a scene change is not detected in the moving image. . As a result, it is possible to prevent the image from being rapidly changed due to the haze removal, and it is possible to suppress the occurrence of a phenomenon such as so-called flicker.
- the scene control unit 300 changes the intensity of haze removal stepwise over a smaller number of frames than in the case where a scene change is not detected in the moving image.
- the parameters used for the haze removal process are generated to Then, when a scene change is detected in the moving image by using the parameters generated by the scene control unit 300, the haze removing unit 400 uses a smaller number of frames than in the case where a scene change is not detected in the moving image.
- the intensity of haze removal is changed stepwise over the course of time.
- the image processing system 100 may not include the scene control unit 300.
- the haze removing unit 400 removes the haze from the input image based on the estimated value of the haze concentration of the image derived by the haze concentration estimating unit 200.
- highly accurate haze removal processing based on the haze concentration estimated by the haze concentration estimation unit 200 can be realized.
- FIG. 2 schematically illustrates an example of a functional configuration of the haze concentration estimation unit 200.
- the haze concentration estimation unit 200 includes a flat and strong edge pixel extraction unit 202, an average luminance calculation unit 204, an average saturation calculation unit 206, a contrast calculation unit 208, a maximum saturation acquisition unit 210, a weighting acquisition unit 212, and a haze concentration calculation unit
- a tool screen determination unit 216 and a selector 218 are provided.
- the flat and strong edge pixel extraction unit 202 extracts pixels that are neither flat nor strong edge from the image input by the image input unit 110.
- the flat & strong edge pixel extraction unit 202 extracts, for example, pixels that are flat or strong edge from the image and excludes the extracted pixels from the image, thereby extracting pixels that are neither flat nor strong edge.
- the flat and strong edge pixel extraction unit 202 may be an example of a first pixel extraction unit.
- the average luminance calculation unit 204 calculates an average luminance value (which may be described as AVE Y ) of pixels which are neither flat nor strong edge.
- the average luminance value may be an example of an evaluation value of luminance.
- the average luminance calculating unit 204 may be an example of a luminance evaluation value deriving unit.
- Average saturation calculation unit 206 calculates the average saturation of the pixels nor flat even strong edges (sometimes referred to as AVE S.).
- the average saturation value may be an example of a saturation evaluation value.
- the average saturation calculating unit 206 may be an example of a saturation evaluation value deriving unit.
- the contrast calculation unit 208 calculates the contrast value of the pixel which is neither flat nor strong edge.
- the contrast value may be an example of a contrast evaluation value.
- the contrast calculating unit 208 may be an example of a contrast evaluation value deriving unit.
- the contrast calculation unit 208 may generate a histogram of pixels that are neither flat nor strong edges.
- the contrast calculation unit 208 may generate a histogram of any number of bins.
- the contrast calculating unit 208 may calculate the histogram width (which may be described as HIST WIDTH ) by subtracting the minimum value from the maximum value of the generated histogram.
- the contrast calculating unit 208 may subtract the minimum value from the maximum value of the bins whose values exceed the threshold value among the plurality of bins.
- HIST WIDTH may be an example of a contrast value.
- the contrast calculating unit 208 may output the number of bins of the histogram as the maximum width of the histogram (which may be described as MAX WIDTH ).
- the maximum saturation acquisition unit 210 acquires the maximum saturation (which may be described as MAX S ) in the image processing system 100.
- the weighting acquisition unit 212 acquires a weighting value (which may be described as coef) used when calculating the haze density of the image.
- the weighting acquisition unit 212 acquires, for example, coef designated by the manufacturer or user of the image processing system 100.
- the haze concentration calculation unit 214 calculates an estimated value (may be described as strength) of the haze concentration of the image.
- the haze density calculation unit 214 may calculate the strength based on the evaluation value of the luminance, the evaluation value of the saturation, and the evaluation value of the contrast of the pixel which is neither flat nor strong edge.
- the haze density calculation unit 214 is based on the average luminance value calculated by the average luminance calculation unit 204, the average saturation value calculated by the average saturation calculation unit 206, and the contrast value calculated by the contrast calculation unit 208.
- the strength may be calculated.
- the haze density calculation unit 214 may calculate Strength by multiplying the average luminance value, the average saturation value, and the contrast value.
- the haze density calculation unit 214 may multiply the average saturation value, the value obtained by subtracting the average saturation value from the maximum saturation, and the value obtained by subtracting the contrast value from the maximum width of the histogram.
- the haze density calculation unit 214 may weight the average luminance value. For example, the haze density calculation unit 214 may perform weighting such that the higher the value, the higher the value, and the lower the value, the lower the value. In addition, the haze density calculation unit 214 may weight the average saturation value. For example, the haze density calculation unit 214 may perform weighting such that the higher the value, the higher the value, and the lower the value, the lower the value.
- the haze concentration calculation unit 214 calculates the strength, for example, according to the following equation 1.
- the haze density calculation unit 214 can derive an estimated value of haze density that is higher as the average luminance value is higher, and can derive an estimated value of haze density that is higher as the average saturation value is lower.
- the lower the value the higher the haze concentration estimate can be derived. Since the assumption that the image contrast is low, the average luminance is high, and the average saturation is low when the haze concentration of the image is high, according to the haze concentration calculation unit 214, the haze characteristic is reflected It is possible to calculate the estimated value of the haze concentration with high accuracy.
- the tool screen determination unit 216 determines whether the input image is a tool screen.
- the tool screen is, for example, a screen for setting display parameters of the display unit 120 and a screen for setting display parameters of an image.
- the haze removing unit 400 executes the haze removing process.
- the viewer of the surveillance camera image displays the tool screen to change the setting of the display parameter while the display unit 120 is displaying the surveillance camera image
- the haze removal process is performed on the tool screen. If it is executed, the screen may darken or flicker unnecessarily.
- the haze concentration estimation unit 200 when the input image is determined to be a tool screen, the haze concentration estimation unit 200 according to the present embodiment outputs 0 as an estimated value of haze concentration, and the input image is determined to be a tool screen. If not, control is performed so as to output the strength calculated by the haze concentration calculation unit 214.
- the selector 218 receives the strength calculated by the haze density calculation unit 214 and the tool screen determination result by the tool screen determination unit 216, and if the input image is not a tool screen, the scene It is output to the control unit 300 or the haze removing unit 400, and when the input image is a tool screen, 0 is output to the scene control unit 300 or the haze removing unit 400.
- the haze removing unit 400 can determine that the input image is a tool screen.
- the haze removing unit 400 may decide not to execute the haze removing process.
- the haze concentration estimation unit 200 may output an estimated value of low value instead of outputting 0.
- the haze concentration estimation unit 200 outputs an estimated value of a value lower than the minimum value of Strength calculated by the haze concentration calculation unit 214.
- the tool screen determination unit 216 may determine whether or not the input image is a tool screen, based on the pixels extracted by the flat and strong edge pixel extraction unit 202 which are neither flat nor strong edge.
- the flat & strong edge pixel extraction unit 202 is a first reference for extracting pixels that are neither flat nor strong edge, which are output to the average luminance calculation unit 204, the average saturation calculation unit 206, and the contrast calculation unit 208. May extract pixels that are neither flat nor strong edge and output to the tool screen determination unit 216 according to different second criteria.
- the second reference may be a reference that is less likely to be determined as a pixel that is neither flat nor strong edge as compared to the first reference.
- the flat and strong edge pixel extraction unit 202 may be an example of a second pixel extraction unit.
- the tool screen determination unit 216 determines that the tool screen is not the tool screen if the ratio of pixels having neither flat nor strong edge received from the flat & strong edge pixel extraction unit 202 to all the pixels of the input image is equal to or less than a predetermined threshold. If it is determined that the screen is larger than a predetermined threshold, it may be determined that the screen is a tool screen.
- the tool screen determination unit 216 sets the ratio of the pixels having flat or strong edges extracted according to the second standard to the pixels having flat or strong edges extracted according to the first standard to be a predetermined threshold. In the following cases, it may be determined that it is a tool screen, and if it is larger than a predetermined threshold, it may be determined that it is not a tool screen.
- the tool screen determination unit 216 even if the screen has a small ratio of pixels having neither flat nor strong edge in the input image, it is determined even if it is a screen of another type, not limited to the tool screen. be able to. For example, according to the tool screen determination unit 216, it can be determined whether or not the input image is an image having a high ratio of an area other than the image display area in the entire display area of the display unit 120.
- the tool screen determination unit 216 may be an example of a haze removal processing target determination unit that determines whether or not the input image is a target on which the haze removal processing is to be performed.
- the average luminance calculation unit 204, the average saturation calculation unit 206, and the contrast calculation unit 208 calculate the average luminance value, the average saturation value, and the contrast value of pixels that are neither flat nor strong edge
- the average luminance calculation unit 204, the average saturation calculation unit 206, and the contrast calculation unit 208 may calculate the average luminance value, the average saturation value, and the contrast value of the entire input image. Further, the average luminance calculating unit 204, the average saturation calculating unit 206, and the contrast calculating unit 208 may calculate an average luminance value, an average saturation value, and a contrast value of a part of the input image.
- FIG. 3 is a diagram for explaining an example of flat and strong edge pixel extraction processing.
- the flat & strong edge pixel extraction unit 202 determines whether the target pixel 230 is flat or strong edge, first, the maximum value and the minimum value of the pixel values for seven pixels in the vertical and horizontal directions centering on the target pixel 230 To get
- the flat & strong edge pixel extraction unit 202 calculates a value obtained by subtracting the minimum value from the maximum value for each of 7 pixels in the vertical direction and 7 pixels in the horizontal direction. Then, the flat & strong edge pixel extraction unit 202 determines that the value obtained by subtracting the minimum value from the maximum value in at least one of the vertical direction and the horizontal direction is equal to or less than the first threshold, and a value larger than the first threshold. If it is equal to or greater than the second threshold value, the pixel of interest 230 is determined as a pixel that is flat or strong edge.
- the number of pixels in the vertical direction and the number of pixels in the horizontal direction may be other than seven.
- the flat & strong edge pixel extraction unit 202 may use the first threshold and the second threshold when extracting pixels that are flat or strong according to the first reference, and flat or strong edge according to the second reference When extracting the pixel which is, a third threshold larger than the first threshold and smaller than the second threshold, and a fourth threshold larger than the third threshold and smaller than the second threshold may be used.
- FIG. 4A schematically illustrates an example weighting graph 240.
- FIG. 4B schematically illustrates an example of the weighting graph 242.
- the weighting graph 240 shows an example of a weighting value used when the haze concentration calculator 214 weights the average luminance value.
- 4A and 4B illustrate the case where the input signal is 10 bits.
- the haze density calculation unit 214 weights the average luminance value according to the weighting graph 240 so that the higher the average luminance value, the higher the value, and the lower the average luminance value, the lower the weight. Can.
- the haze density calculator 214 may use the weighting graph 240 also when weighting the average saturation value.
- the haze density calculation unit 214 may use the weighting graph 240 having the same value when weighting the average luminance value and weighting the average saturation value, and the weighting graph 240 may have different values. May be used. For example, when weighting of the average luminance value is made heavier than the average saturation value, as shown in the weighting graph 242, the haze density calculation unit 214 uses the weighting graph 242 in which the weighting is heavier, to the average luminance value. It may be weighted.
- FIG. 5 is a diagram for explaining the histogram value.
- FIG. 5 exemplifies a case where the number of histogram bins is 16.
- the contrast calculating unit 208 may calculate the HIST WIDTH by subtracting the minimum value from the maximum value of the bins whose values exceed the threshold value among the plurality of bins, as shown in FIG.
- FIG. 6 schematically illustrates an example of a functional configuration of the scene control unit 300.
- the scene control unit 300 includes a scene change determination unit 310, a haze reliability estimation unit 330, and a haze removal parameter adjustment unit 360.
- the scene change determination unit 310 determines whether the moving image input by the image input unit 110 includes a scene change.
- the scene change determination unit 310 may associate a scene change flag indicating whether the frame is a scene changed frame for each of a plurality of frames included in the moving image.
- the haze reliability estimation unit 330 estimates the reliability of the strength output from the haze concentration estimation unit 200 for the frame included in the moving image input by the image input unit 110.
- the haze removal parameter adjustment unit 360 is used for the haze removal process for a plurality of frames included in the moving image, based on the reliability estimated by the haze reliability estimation unit 330 and the scene change flag generated by the scene change determination unit 310. The parameters are adjusted and output to the haze removing unit 400.
- FIG. 7 schematically illustrates an example of a functional configuration of the scene change determination unit 310.
- the scene change determination unit 310 includes a high saturation pixel extraction unit 312, a hue histogram generation unit 314, a high saturation pixel rate measurement unit 316, a flat & strong edge pixel extraction unit 318, an average luminance calculation unit 320, an average saturation calculation unit 322, and determination processing.
- a unit 324 is provided.
- the high saturation pixel extraction unit 312 extracts high saturation pixels from one of the plurality of frames included in the moving image input by the image input unit 110.
- the high saturation pixel may be a pixel whose saturation is higher than a predetermined threshold.
- the high saturation pixel extraction unit 312 receives RGB data, the difference between the maximum value and the minimum value of the R component, the G component, and the B component for each of the plurality of pixels included in the frame is equal to or greater than a predetermined threshold. Certain pixels may be extracted as high saturation pixels.
- the high saturation pixel extraction unit 312 may extract, for each of the plurality of pixels included in the frame, a pixel whose S component is equal to or greater than a predetermined threshold as a high saturation pixel.
- the hue histogram generation unit 314 generates a histogram of hue (which may be described as “HueHIST”) for the high saturation pixels extracted by the high saturation pixel extraction unit 312.
- HueHIST a histogram of hue
- the hue histogram generation unit 314 may generate HueHIST for a frame included in the moving image input by the image input unit 110.
- the high saturation pixel rate measuring unit 316 measures a high saturation pixel rate (which may be described as HighSatRate) indicating the proportion of high saturation pixels in one frame.
- the high saturation pixel rate measuring unit 316 may set the ratio of light saturation pixels to all the pixels of one frame as HighSatRate.
- the high saturation pixel rate measuring unit 316 may be an example of a high saturation pixel rate deriving unit that derives the high saturation pixel rate in one frame.
- the flat and strong edge pixel extraction unit 318 extracts a pixel that is neither flat nor strong edge from one frame of the plurality of frames included in the moving image input by the image input unit 110.
- the flat and strong edge pixel extraction unit 318 may extract pixels that are neither flat nor strong edge as the flat and strong edge pixel extraction unit 202 does.
- the flat & strong edge pixel extraction unit 318 may extract pixels which are neither flat nor strong edge according to the first reference, and may extract pixels which are neither flat nor strong edge according to the second reference Also, pixels that are neither flat nor strong edges may be extracted according to other criteria.
- the average luminance calculation unit 320 calculates AVE Y of the pixel which is neither flat nor strong edge extracted by the flat & strong edge pixel extraction unit 318.
- the average luminance calculation unit 320 calculates the AVE Y of the pixel having neither flat nor strong edge extracted by the flat & strong edge pixel extraction unit 318.
- the average luminance calculation unit 320 may calculate AVE Y for a frame included in the moving image input by the image input unit 110.
- Average saturation calculation unit 322 calculates the AVE S pixel nor a strong edge in a flat extracted by flat & strong edge pixel extraction unit 318.
- the average color saturation calculation unit 322 will be described as an example a case of calculating the AVE S pixel nor a strong edge in a flat extracted by flat & strong edge pixel extraction unit 318, to Not exclusively.
- Average saturation calculator 322 the frame included in the moving image input by the image input unit 110 may calculate the AVE S.
- the determination processing unit 324 executes a determination process of determining whether a moving image input by the image input unit 110 includes a scene change.
- the determination processing unit 324 generates a scene change flag indicating whether the frame is a scene-changed frame, and outputs the scene change flag to the haze removal parameter adjustment unit 360.
- the determination processing unit 324 determines whether the moving image includes a scene change based on different criteria depending on whether the high saturation pixel ratio measured by the high saturation pixel ratio measuring unit 316 is higher than a predetermined threshold. You may judge.
- the determination processing unit 324 determines the hue of the one frame and the past frames of the one frame. Whether or not a scene change is included in the moving image may be determined based on the hue of.
- the past frame of the one frame is, for example, a frame before the one frame.
- the determination processing unit 324 performs SAD of HueHIST of the one frame generated by the hue histogram generation unit 314 and hue histogram of the previous frame of the one frame (which may be described as HueHIST_dl). Based on (Sum of Absolute Difference) (which may be described as HueHISTSAD), it may be determined whether the moving image includes a scene change.
- determination processing unit 324 HueHISTSAD is lower than the fifth threshold value, the average luminance value of the past frame AVE Y and the one frame of the one frame (may be described as AVE Y _dl.) And the The difference absolute value is lower than the sixth threshold, and the difference absolute value between the AVE S of the one frame and the average saturation value (may be described as AVE S dl) of the past frames of the one frame is the sixth. If it is lower than the seven threshold, it is determined that the one frame is not a scene-changed frame, and otherwise, it is determined that the one frame is a scene-changed frame.
- the scene change flag of the one frame may be set to False. If the determination processing unit 324 determines that the one frame is a scene-changed frame, the scene change flag of the one frame may be set to True.
- the determination processing unit 324 determines HighSatRate of the one frame and the past frames of the one frame. Based on the high saturation pixel rate (which may be described as HighSatRate_dl), it may be determined whether the moving image includes a scene change.
- a difference absolute value between HighSatRate and HighSatRate_dl is lower than the eighth threshold value
- the difference absolute value between the AVE Y and AVE Y _dl is lower than the sixth threshold value
- the difference between the AVE S and AVE S _dl If the absolute value is lower than the seventh threshold value, it is determined that the one frame is a scene-changed frame, and if not, it is determined that the one frame is a scene-changed frame.
- FIG. 8 schematically illustrates an example of a functional configuration of the haze reliability estimation unit 330.
- the haze reliability estimation unit 330 includes a flat & strong edge pixel extraction unit 332, an average luminance calculation unit 334, a high saturation pixel extraction unit 336, a high saturation pixel rate measurement unit 338, a haze concentration estimated value acquisition unit 340 and a reliability calculation unit 342. Prepare.
- the flat and strong edge pixel extraction unit 332 extracts a pixel that is neither flat nor strong edge from one frame among a plurality of frames included in the moving image input by the image input unit 110.
- the flat and strong edge pixel extraction unit 332 may extract pixels that are neither flat nor strong edge as the flat and strong edge pixel extraction unit 202 does.
- the flat & strong edge pixel extraction unit 332 may extract pixels which are neither flat nor strong edge according to the first reference, and may extract pixels which are neither flat nor strong edge according to the second reference Also, pixels that are neither flat nor strong edges may be extracted according to other criteria.
- the average luminance calculation unit 334 calculates the AVE Y of the pixel which is neither flat nor strong edge extracted by the flat & strong edge pixel extraction unit 332.
- the average luminance calculation unit 334 may calculate AVE Y for a frame included in the moving image input by the image input unit 110.
- the high saturation pixel extraction unit 336 extracts a high saturation pixel from one of a plurality of frames included in the moving image input by the image input unit 110.
- the high saturation pixel extraction unit 336 extracts, as high saturation pixels, pixels in which the difference between the maximum value and the minimum value of the R component, the G component, and the B component for each of the plurality of pixels included in the frame is a predetermined threshold or more. You may
- the high saturation pixel rate measuring unit 338 measures HighSatRate in one frame.
- the haze concentration estimated value acquisition unit 340 acquires the strength output from the haze concentration estimation unit 200.
- the reliability calculation unit 342 calculates the reliability of the strength acquired by the haze concentration estimated value acquisition unit 340 based on AVE Y calculated by the average luminance calculation unit 334 and HighSatRate measured by the high saturation pixel rate measurement unit 338. And output to the haze removal parameter adjustment unit 360.
- the reliability calculation unit 342 may be an example of a reliability derivation unit that derives the reliability of the strength based on AVE Y and HighSatRate.
- the reliability calculation unit 342 may calculate the reliability of Strength based on different criteria depending on whether the Strength acquired by the haze concentration estimated value acquisition unit 340 is larger than a predetermined threshold.
- the reliability calculation unit 342 calculates higher reliability as the AVE Y is larger, and higher reliability as the HighSatRate is lower, when the strength acquired by the haze concentration estimated value acquisition unit 340 is larger than a predetermined threshold. You may calculate In addition, when the strength acquired by the haze concentration estimated value acquisition unit 340 is equal to or less than a predetermined threshold, the reliability calculation unit 342 calculates higher reliability as the AVE Y is smaller, and higher reliability as the HighSatRate is higher. You may calculate the degree.
- the degree of reliability calculation unit 342 determines the strength acquired by the estimated haze value acquisition unit 340, AVE Y calculated by the average luminance calculation unit 334, and the high saturation pixel rate measurement unit 338. Each of HighSatRate measured is weighted.
- the reliability calculation unit 342 weights the Strength and HighSatRate such that the higher the value, the higher the value, and the lower the value, the lower the value. Also, for example, with respect to AVE Y , the reliability calculation unit 342 performs weighting such that the higher the value, the lower the value, and the lower the value, the higher the value.
- the weighted Strength may be described as StrengthWeight.
- the AVE Y in which the weighting may be referred to as AVE Y Weight.
- the weighted HighSatRate may be described as HighSatRateWeight.
- the reliability calculation unit 342 sets the larger one of AVE Y Weight and HighSatRateWeight as EvalMax. Then, the reliability calculation unit 342 calculates the absolute value of the difference between EvalMax and StrengthWeight as the reliability of the estimated value of the haze concentration.
- FIG. 9 schematically illustrates an example of the weighting graph 352.
- the weighting graph 352 shows an example of weighting values used when the reliability calculation unit 342 weights the strength. By weighting the Strength according to the weighting graph 352, the reliability calculation unit 342 can perform weighting such that the higher the Strength, the higher the value, and the lower the Strength, the lower the value.
- the weighting graph 352 may be used when the reliability calculation unit 342 weights HighSatRate.
- FIG. 10 schematically illustrates an example of the weighting graph 354.
- the weighting graph 354 shows an example of weighting values used when the reliability calculation unit 342 weights AVE Y.
- the reliability calculation unit 342 By weighting the AVE Y according to the weighting graph 354 by the reliability calculation unit 342, the higher the AVE Y, the lower the value, and the lower the Strength, the higher the value.
- FIG. 11 schematically illustrates an example of a functional configuration of the haze removal parameter adjustment unit 360.
- the haze removal parameter adjustment unit 360 includes a haze concentration target value calculation unit 362 and a parameter adjustment unit 364.
- the haze density target value calculation unit 362 calculates a haze density target value (which may be described as TargetDepth) for one frame.
- TargetDepth indicates a haze removal parameter to be converged when the contents of one frame and a plurality of frames following the one frame do not change.
- the haze density target value calculation unit 362 calculates TargetDepth (which may be described as Target Depth_dl) of a past frame of the one frame, Strength and reliability of the one frame received from the haze concentration estimation unit 200. Based on the reliability of the strength received from the calculation unit 342 and the scene change flag for the one frame received from the determination processing unit 324, TargetDepth for the one frame may be determined.
- the haze density target value calculation unit 362 calculates a difference absolute value (which may be described as DiffDepth) between Strength and TargetDepth_dl. Then, when the DiffDepth is greater than the ninth threshold and the reliability of the Strength is greater than the tenth threshold, and the scene change flag is True, the haze density target value calculation unit 362 sets the Strength as the TargetDepth, and other than that. In this case, TargetDepth_dl is set as TargetDepth.
- DiffDepth a difference absolute value between Strength and TargetDepth_dl.
- the parameter adjustment unit 364 determines the parameter (which may be referred to as HazeRemovalStrength) used for the haze removal processing of the one frame, as the Strength or TargetDepth_dl determined by the haze concentration target value calculation unit 362 as the TargetDepth of the one frame. Adjust so as to gradually approach the value corresponding to
- the parameter adjustment unit 364 is an absolute difference between the TargetDepth determined by the haze concentration target value calculation unit 362 and the parameter (described as HazeRemovalStrength_dl) used for the haze removal process of the past frame of the one frame.
- the HazeRemovalStrength is determined by the haze density target value calculation unit 362 as the TargetDepth of the one frame by the value (which may be described as DiffStrength), the reliability of the Strength, and the adjustment amount according to the scene change flag.
- the value corresponding to the strength or target depth dl may be adjusted stepwise.
- the parameter adjustment unit 364 corresponds to the strength or TargetDepth_dl determined with the HazeRemovalStrength as the TargetDepth of the one frame by the haze density target value calculation unit 362 using the first adjustment amount. Adjust so that it approaches the value in stages.
- the parameter adjustment unit 364 sets HazeRemovalStrength as the second adjustment amount. Adjust to gradually approach values corresponding to Strength or TargetDepth_dl determined as TargetDepth of the frame of.
- the parameter adjustment unit 364 adjusts the HazeRemovalStrength to be gradually closer to the value corresponding to the Strength or TargetDepth_dl determined as the TargetDepth of the one frame in the third adjustment amount in other cases.
- the first adjustment amount is larger than the second adjustment amount and the third adjustment amount
- the second adjustment amount is larger than the third adjustment amount.
- the haze density target value calculation unit 362 uses either TargetDepth_dl or Strength for the haze removal processing based on the reliability of Strength and the absolute value of the difference between Strength and TargetDepth_dl, or a scene change flag. It may be decided to use it to adjust the parameters.
- the haze density target value calculation unit 362 that acquires TargetDepth_dl may be an example of a target value acquisition unit.
- the haze density target value calculation unit 362 may be an example of a difference absolute value deriving unit that calculates the difference absolute value between Strength and TargetDepth_dl.
- the haze density target value calculation unit 362 may be an example of a target value determination unit that determines TargetDepth for the one frame.
- FIG. 12 schematically illustrates an example of a functional configuration of the haze removing unit 400.
- the haze removing unit 400 includes an illumination light separating unit 402, a parameter acquiring unit 410, a removing processing unit 420, and a combining unit 426.
- Illumination light separating unit 402 separates the illumination light component I L from the image I inputted by the image input unit 110. Illumination light separating unit 402, if it is possible to separate the illumination light component I L from the image I, may be carried out any process.
- the illumination light separating unit 402 uses the edge-preserving low-pass filter, for separating the illumination light component I L from the image I.
- the edge preserving low pass filter is a filter that performs smoothing while preserving edges.
- the illumination light separation unit 402 uses, for example, a bilateral filter as an edge-preserving low-pass filter.
- the illumination light separation unit 402 may output the illumination light component IL and the image I to the parameter acquisition unit 410.
- the parameter acquisition unit 410 acquires a parameter used for haze removal.
- the parameter acquisition unit 410 includes an atmospheric light calculation unit 412, a transmittance calculation unit 414, and a haze concentration estimated value acquisition unit 416.
- the atmospheric light calculation unit 412 calculates the atmospheric light A of the image I.
- the atmospheric light calculation unit 412 may perform any process as long as the atmospheric light A of the image I can be calculated. For example, the atmospheric light calculation unit 412 first calculates, for each pixel of the image I, the minimum value of RGB including peripheral pixels. Next, the atmospheric light calculation unit 412 extracts, from the image I, the pixel having the highest calculated 0.1%. Then, the atmospheric light calculation unit 412 sets the value of the pixel having the highest luminance among the extracted pixels as the atmospheric light A.
- the transmittance calculation unit 414 calculates the transmittance t corresponding to the haze density for each of a plurality of pixels of the image input by the image input unit 110.
- the transmittance calculating unit 414 may be an example of a transmittance deriving unit.
- the transmittance calculation unit 414 may perform any process as long as the transmittance t can be calculated.
- the transmittance calculation unit 414 calculates the transmittance t based on the Dark Channel Prior (sometimes referred to as DCP) represented by the following Equation 2.
- I C is the color channel of I
- ⁇ (x) is a local region centered at x.
- the transmittance calculation unit 414 may calculate the transmittance t from the value of DCP based on the assumption that DCP in Equation 2 represents the transmittance t. For example, the transmittance calculation unit 414 may calculate the transmittance t by Equation 3 below.
- the haze concentration estimated value acquisition unit 416 acquires the strength output from the haze concentration estimation unit 200.
- the parameter acquisition unit 410 includes the image I, the illumination light component I L , the atmospheric light A calculated by the atmospheric light calculation unit 412, the transmittance t calculated by the transmittance calculation unit 414, and the strength acquired by the estimated haze concentration value acquisition unit 416. Is output to the removal processing unit.
- the removal processing unit 420 executes a haze removal process on the image I based on Retinex theory represented by the following Equation 4 and an atmospheric model of a haze image represented by the following Equation 5.
- the removal processing unit 420 may execute the haze removal processing using the atmospheric model of the haze image and the Retinex theory, on the assumption that the reflectance component included in the atmospheric light is small or can be approximated. .
- the reflectance component included in the atmospheric light is a minimum, it can be considered that the following equation 8 holds.
- the removal processing unit 420 further presupposes that the atmospheric model can be applied only to the respective illumination light components with respect to the atmospheric light, the original image, and the input image, the atmospheric model of the haze image and the Retinex theory
- the haze removal process may be performed using this method. According to such a premise, the following equation 9 is established.
- Equation 10 By applying Equations 8 and 9 to Equation 7, the following Equation 10 is obtained.
- the removal processing unit 420 may perform haze removal processing with different degrees of haze removal on the reflectance component and the illumination light component. For example, the removal processing unit 420 may make the degree of removal of haze different by changing the transmittance t with respect to Equations 9 and 10 described above. Further, the removal processing unit 420 may make the degree of removal of haze different by weighting the results of Equation 9 and Equation 10 differently.
- the removal processing unit 420 includes an illumination light component processing unit 422 and a reflectance component processing unit 424.
- the illumination light component processing unit 422 performs a haze removal process on the illumination light component of the image.
- the reflectance component processing unit 424 performs a haze removal process on the reflectance component of the image.
- the illumination light component processing unit 422 may execute the haze removal processing using the HazeRemovalStrength received from the parameter adjustment unit 364. For example, the illumination light component processing unit 422 may calculate the illumination light component J L subjected to the haze removal processing using the illumination light component I L , the atmospheric light A, the transmittance t, HazeRemovalStrength, and Equation 9 above. The illumination light component processing unit 422 may adjust the transmittance t using HazeRemovalStrength. In addition, the illumination light component processing unit 422 may use HazeRemovalStrength instead of the transmittance t. Further, the illumination light component processing unit 422 may use a value based on HazeRemovalStrength instead of the transmittance t.
- the parameter acquisition unit 410 may not have the haze concentration estimated value acquisition unit 416.
- the haze concentration estimated value acquisition unit 416 may receive HazeRemovalStrength from the parameter adjustment unit 364 and may transmit the received HazeRemovalStrength to the removal processing unit 420.
- the illumination light component processing unit 422 receives the illumination light component I received from the parameter acquisition unit 410 when the still image is input by the image input unit 110 or when the image processing system 100 does not include the scene control unit 300.
- the illumination light component J L subjected to the haze removal processing may be calculated using L 1 , atmospheric light A, transmissivity t, strength, and Equation 9 above.
- the illumination light component processing unit 422 may calculate the illumination light component J L by applying Strength to the transmittance t. For example, the illumination light component processing unit 422 multiplies the transmission factor t by the strength. Also, for example, the illumination light component processing unit 422 may perform weighting on the transmittance t according to the value of Strength. As a result, it is possible to realize more accurate haze removal processing using the strength estimated by the haze concentration estimation unit 200.
- Reflectance component processor unit 424 from the image I and the illumination light component I L received from the parameter acquisition unit 410 may calculate the reflectance component I R.
- the reflectance component processing unit 424 may execute the haze removal processing using the HazeRemovalStrength received from the parameter adjustment unit 364. For example, the reflectance component processing unit 424 calculates the reflectance component J R subjected to the haze removal processing using the illumination light component I L , the reflectance component I R , the transmittance t, the HazeRemovalStrength, and the formula 10 above. Good.
- the reflectance component processing unit 424 may adjust the transmittance t using HazeRemovalStrength.
- the reflectance component processing unit 424 may use HazeRemovalStrength instead of the transmittance t. Also, the reflectance component processing unit 424 may use a value based on HazeRemovalStrength instead of the transmittance t.
- the parameter acquisition unit 410 may not have the haze concentration estimated value acquisition unit 416.
- the haze concentration estimated value acquisition unit 416 may receive the HazeRemovalStrength from the parameter adjustment unit 364 and may transmit the received HazeRemovalStrength to the removal processing unit 420.
- the reflectance component processing unit 424 receives the illumination light component I L and the reflectance component I R when the still image is input by the image input unit 110 or when the image processing system 100 does not include the scene control unit 300.
- the transmittance R , the strength, and the JR subjected to the haze removal processing may be calculated using the above equation (10).
- Reflectance component processing unit 424 applies the Strength transmittance t may calculate the J R.
- the reflectance component processing unit 424 multiplies the transmittance t by the strength.
- the reflectance component processing unit 424 may perform weighting on the transmittance t in accordance with the value of Strength. As a result, it is possible to realize more accurate haze removal processing using the strength estimated by the haze concentration estimation unit 200.
- the combining unit 426 combines the illumination light component J L subjected to the haze removal processing by the illumination light component processing unit 422 and the reflectance component J R subjected to the haze removal processing by the reflectance component processing unit 424.
- the synthesizing unit 426 generates an output image J by synthesizing J L and J R.
- the output image J generated by the combining unit 426 may be displayed by the display unit 120.
- the image processing system 100 is described as a display device including the haze density estimation unit 200, the scene control unit 300, and the haze removal unit 400 as an example, but the present invention is not limited thereto.
- the image processing system 100 may be a display device including at least one of the haze density estimation unit 200, the scene control unit 300, and the haze removal unit 400.
- the image processing system 100 is a display device including only the scene change determination unit 310 among the scene change determination unit 310, the haze reliability estimation unit 330, and the haze removal parameter adjustment unit 360 included in the scene control unit 300.
- the image processing system 100 may be a display device including only the haze reliability estimation unit 330.
- the haze concentration estimated value acquiring unit 340 may acquire the haze concentration estimated value estimated by another device or the like instead of the strength output by the haze concentration estimating unit 200.
- the image processing system 100 is a display device including only the haze removing unit 400 among the haze concentration estimating unit 200, the scene control unit 300, and the haze removing unit 400
- the haze concentration estimated value acquiring unit 416 instead of the strength output by the estimation unit 200, a haze concentration estimated value estimated by another device or the like may be acquired.
- the image processing system 100 is a display device
- the present invention is not limited to this.
- Other types of devices may be used as long as the device processes an image.
- the image processing system 100 may be a mobile phone such as a smartphone, a tablet terminal, a personal computer, and an information home appliance.
- the image processing system 100 may be a device that does not have the display unit 120 and causes an external display unit to display an image.
- each unit of the image processing system 100 may be realized by hardware or may be realized by software. Also, it may be realized by a combination of hardware and software.
- the computer may function as the image processing system 100 by executing the program.
- the program may be installed on a computer that constitutes at least a part of the image processing system 100 from a computer readable medium or a storage device connected to a network.
- the program installed in the computer and causing the computer to function as the image processing system 100 causes the CPU or the like to cause the computer to function as each part of the image processing system 100.
- the information processing described in these programs functions as a concrete means in which software and hardware resources of the image processing system 100 cooperate by being read into a computer.
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Abstract
Description
[先行技術文献]
[特許文献]
[特許文献1]特開2012-168936号公報
Claims (20)
- 画像の少なくとも一部の領域の輝度の評価値を導出する輝度評価値導出部と、
前記領域の彩度の評価値を導出する彩度評価値導出部と、
前記領域のコントラストの評価値を導出するコントラスト評価値導出部と、
前記輝度の評価値、前記彩度の評価値及び前記コントラストの評価値に基づいて、前記画像のヘイズ濃度の推定値を導出するヘイズ濃度推定部と
を備える画像処理システム。 - 前記画像から平坦でも強エッジでもない画素を抽出する第1画素抽出部
を更に備え、
前記ヘイズ濃度推定部は、前記第1画素抽出部によって抽出された前記平坦でも強エッジでもない画素の輝度の評価値、彩度の評価値及びコントラストの評価値に基づいて、前記ヘイズ濃度の推定値を導出する、請求項1に記載の画像処理システム。 - 画像から平坦でも強エッジでもない画素を抽出する第1画素抽出部と、
前記第1画素抽出部によって抽出された前記平坦でも強エッジでもない画素の輝度の評価値、彩度の評価値及びコントラストの評価値の少なくとも2つに基づいて、前記画像のヘイズ濃度の推定値を導出するヘイズ濃度推定部と
を備える画像処理システム。 - 前記輝度の評価値は、前記領域の平均輝度値であり、
前記彩度の評価値は、前記領域の平均彩度値であり、
前記コントラストの評価値は、前記領域のコントラスト値であり、
前記ヘイズ濃度推定部は、前記平均輝度値が高いほど高い値の前記ヘイズ濃度の推定値を導出し、前記平均彩度値が低いほど高い値の前記ヘイズ濃度の推定値を導出し、前記コントラスト値が低いほど高い値の前記ヘイズ濃度の推定値を導出する、請求項1に記載の画像処理システム。 - 前記画像は複数のフレームを含む動画であり、
前記複数のフレームのうちの一のフレームにおける、彩度が予め定められた閾値より高い高彩度画素を抽出する高彩度画素抽出部と、
前記一のフレームにおける前記高彩度画素の割合を示す高彩度画素率を導出する高彩度画素率導出部と、
前記高彩度画素率が予め定められた閾値より高いか否かに応じて、異なる基準に基づいて、前記画像にシーンチェンジが含まれるか否かを判定するシーンチェンジ判定部と
を更に備える、請求項1から4のいずれか一項に記載の画像処理システム。 - 前記一のフレームにおける前記高彩度画素率と、前記一のフレームの平均輝度値とに基づいて、前記一のフレームの前記ヘイズ濃度の推定値の信頼度を導出する信頼度導出部
を更に備える、請求項5に記載の画像処理システム。 - 前記信頼度導出部が導出した前記一のフレームのヘイズ濃度の推定値の信頼度と、前記一のフレームがシーンチェンジしたフレームであるかを示すシーンチェンジフラグとに基づいて、前記一のフレームに対するヘイズ除去処理に用いるパラメータを調整するパラメータ調整部
を更に備える、請求項6に記載の画像処理システム。 - 前記画像の複数の画素毎のヘイズ濃度に対応する透過率を導出する透過率導出部と、
前記ヘイズ濃度の推定値及び前記透過率に基づいて、前記画像にヘイズ除去処理を実行するヘイズ除去部と
を更に備える、請求項1から4のいずれか一項に記載の画像処理システム。 - 前記画像から平坦でも強エッジでもない画素を抽出する第2画素抽出部
をさらに備え、
前記ヘイズ除去部は、前記第2画素抽出部によって抽出された前記平坦でも強エッジでもない画素の、前記画像における割合に基づいて、前記ヘイズ除去処理を実行するか否かを決定する、請求項8に記載の画像処理システム。 - 動画に含まれる複数のフレームのうちの一のフレームから、彩度が予め定められた閾値より高い高彩度画素を抽出する高彩度画素抽出部と、
前記一のフレームにおける前記高彩度画素の割合を示す高彩度画素率を導出する高彩度画素率導出部と、
前記一のフレームにおける前記高彩度画素率が予め定められた閾値より高いか否かに応じて、異なる基準に基づいて、前記動画にシーンチェンジが含まれるか否かを判定するシーンチェンジ判定部と
を備える、画像処理システム。 - 前記シーンチェンジ判定部は、前記高彩度画素率が前記閾値よりも高い場合、前記一のフレームの色相と、前記一のフレームの過去のフレームの色相とに基づいて、前記画像にシーンチェンジが含まれるか否かを判定し、前記高彩度画素率が前記閾値以下の場合、前記一のフレームの高彩度画素率と、前記一のフレームの過去のフレームの高彩度画素率とに基づいて、前記画像にシーンチェンジが含まれるか否かを判定する、請求項10に記載の画像処理システム。
- 前記一のフレームのヘイズ濃度の推定値を取得するヘイズ濃度推定値取得部と、
前記一のフレームにおける前記高彩度画素率と、前記一のフレームの平均輝度値とに基づいて、前記ヘイズ濃度の推定値の信頼度を導出する信頼度導出部と
を更に備える、請求項10又は11に記載の画像処理システム。 - 前記信頼度導出部は、前記推定値が予め定められた閾値よりも高い場合、前記平均輝度値が大きいほど高い信頼度を導出し、かつ、前記高彩度画素率が低いほど高い信頼度を導出し、前記推定値が予め定められた閾値以下の場合、前記平均輝度値が小さいほど高い信頼度を導出し、かつ、前記高彩度画素率が高いほど高い信頼度を導出する、請求項12に記載の画像処理システム。
- 前記一のフレームの過去のフレームのヘイズ濃度目標値を取得する目標値取得部と、
前記信頼度導出部が導出した前記信頼度に基づいて、前記目標値取得部が取得した前記ヘイズ濃度目標値と、前記ヘイズ濃度推定値取得部が取得した前記ヘイズ濃度の推定値とのいずれをヘイズ除去処理に用いるパラメータを調整するために用いるかを決定する目標値決定部と
を更に備える、請求項12又は13に記載の画像処理システム。 - 前記目標値取得部が取得したヘイズ濃度目標値と、前記ヘイズ濃度推定値取得部が取得した前記ヘイズ濃度の推定値との差分絶対値を導出する差分絶対値導出部
を更に備え、
前記目標値決定部は、前記推定値の信頼度及び前記差分絶対値、又は、前記一のフレームがシーンチェンジしたフレームであるかを示すシーンチェンジフラグに基づいて、前記目標値取得部が取得した前記ヘイズ濃度目標値と、前記ヘイズ濃度推定値取得部が取得した前記ヘイズ濃度の推定値とのいずれをヘイズ除去処理に用いるパラメータを調整するために用いるかを決定する、請求項14に記載の画像処理システム。 - 前記一のフレームのヘイズ除去処理に用いるパラメータを、前記目標値決定部によって決定された前記ヘイズ濃度目標値又は前記ヘイズ濃度の推定値に対応する値に段階的に近づけるように調整するパラメータ調整部
を更に備える、請求項14又は15に記載の画像処理システム。 - 前記パラメータ調整部は、前記目標値決定部によって決定された前記ヘイズ濃度目標値又は前記ヘイズ濃度の推定値と、前記一のフレームの過去のフレームのヘイズ除去処理に用いたパラメータとの差分絶対値、前記ヘイズ濃度の推定値の信頼度、及び前記一のフレームがシーンチェンジしたフレームであるかを示すシーンチェンジフラグに応じた調整量で、前記ヘイズ除去処理に用いるパラメータを、前記目標値決定部によって決定された前記ヘイズ濃度目標値又は前記ヘイズ濃度の推定値に対応する値に段階的に近づけるように調整する、請求項16に記載の画像処理システム。
- 画像のヘイズ濃度を取得するヘイズ濃度取得部と、
前記ヘイズ濃度に基づいて、前記画像の反射率成分と前記画像の照明光成分に、ヘイズ除去度がそれぞれ異なるヘイズ除去処理を施す除去処理部と、
前記ヘイズ除去処理が施された前記反射率成分及び前記照明光成分を合成する合成部と
を備え、
前記除去処理部は、大気光に含まれる反射率成分がないと近似できることを前提として、ヘイズ画像の大気モデルとレティネックス理論とを用いて、前記画像の反射率成分と前記画像の照明光成分とに、ヘイズ除去度がそれぞれ異なるヘイズ除去処理を施す、画像処理システム。 - 前記除去処理部は、前記照明光成分のみに対して前記ヘイズ画像の大気モデルが適用できることをさらに前提として、ヘイズ画像の大気モデルとレティネックス理論とを用いて、前記画像の反射率成分と前記画像の照明光成分とに、ヘイズ除去度がそれぞれ異なるヘイズ除去処理を施す、請求項18に記載の画像処理システム。
- コンピュータを、請求項1から19のいずれか一項に記載の画像処理システムとして機能させるためのプログラムを記録したコンピュータ読み取り可能な記録媒体。
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