CN103796017A - Image discriminating device and method - Google Patents
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Abstract
The invention discloses an image discriminating device and method. The device comprises a first coefficient block set generating module, a second coefficient block set generating module, a DCT quantized noise set generating module and a discriminating module, wherein the first coefficient block set generating module is used for segmenting an image and removing subblocks with pixel values being 0 or 255, and DCT conversion is conducted to obtain a first coefficient block set; the second coefficient block set generating module is used for rounding DCT coefficient values in the first coefficient block set and removing all the subblocks with pixel values being 0, and then a second coefficient block set is formed; the DCT quantized noise set generating module is used for obtaining difference values between coefficient values at different positions in the first coefficient block set and the second coefficient block set, and then a DCT quantized noise set is formed; the discriminating module is used for calculating variance of coefficient values in the DCT quantized noise set, and the image is discriminated as a JEPG uncompressed image if the variance is lower than a threshold value. Whether a high-compression-quality image which can not be discriminated in the prior art is a JEPG uncompressed image can be effectively discriminated through the image discriminating device and method.
Description
Technical field
The present invention relates to technical field of image processing, relate in particular to a kind of for differentiating whether image discriminating device and the method for discrimination thereof of jpeg decompression contract drawing picture of image.
Background technology
JPEG(Joint Photographic Experts Group) be the picture format that is widely used in many occasions, because it is easy to store and a large amount of extensive uses of transmission quilt.Jpeg image compression standard is by (the International Telecommunication Union of International Telecommunications Union, ITU), (the International Organization for Standardization of International Standards Organization, and (the International Electrotechnical Commisson of International Electrotechnical Commission ISO), IEC) proposed first in 1988, and obtain rapidly popularization and application.Its encoding-decoding process respectively as depicted in figs. 1 and 2, wherein quantizer is to represent to utilize self-defining quantization step to remove 64 DCT(Discrete Cosine Transform) conversion coefficient, then round, FDCT and IDCT represent respectively forward direction dct transform and inverse dct transform.
A large amount of universal along with the development of computer technology and digital camera, people can take and touch a large amount of pictures more, but simultaneously due to the appearance of the image editing software of various easy operatings, the pictures that are tampered, forge also emerge in multitude more.Fastidious for to image's authenticity especially differentiated and the needs of image true-false all made our GPRS distinguish the ability of image true-false in evidence obtaining process.Wherein, differentiate whether jpeg decompression contract drawing picture has important effect for the detection of distorted image to image.But distort generally from visually producing obvious difference, prior art also cannot look like to differentiate to jpeg decompression contract drawing well, for example as shown in Figure 3, when not compressed image of image
by
composition,
for compressed image not,
for jpeg decompression contract drawing picture, if
compression quality
time, prior art is cannot be to image
idifferentiate.
Therefore, prior art has yet to be improved and developed.
Summary of the invention
In view of above-mentioned the deficiencies in the prior art, the object of the present invention is to provide a kind of image discriminating device and method of discrimination thereof, be intended to solve current problem.
Technical scheme of the present invention is as follows:
A kind of image discriminating device, wherein, described device comprises following part:
The first coefficient block set generation module, for image being divided into continuous nonoverlapping sub-block, searching and remove, to contain pixel value be 0 or 255 sub-block, remaining sub-block carried out respectively to dct transform and obtain the first coefficient block set;
The second coefficient block set generation module, for all DCT coefficient values of described the first coefficient block set are rounded, searches and removes DCT coefficient value in the first coefficient block set after rounding and be all 0 sub-block, forms the second coefficient block set;
DCT quantizing noise set generation module, for the DCT coefficient value of described the first coefficient block set and the second coefficient block set opposite position is got to difference, forms the set of DCT quantizing noise;
Determination module, for calculating the variance yields of all coefficient values of described DCT quantizing noise set, compares this variance yields and default threshold value, if described variance yields is less than threshold value, to look like be JEPG decompressing image to process decision chart.
Described image discriminating device, wherein, described device also comprises:
Image type is differentiated and modular converter, and for carrying out the judgement of image type before image discriminating, in the time that image is RGB coloured image, converted image is YCbCr image.Y component is judged.In the time that image is gray level image, directly use gray value.
An image discriminating method that utilizes image discriminating device as above to carry out, wherein, said method comprising the steps of:
Image is divided into continuous nonoverlapping sub-block by A, described the first coefficient block set generation module, searches and remove that to contain pixel value be 0 or 255 sub-block, remaining sub-block carried out respectively to dct transform and obtain the first coefficient block set;
B, described the second coefficient block set generation module round all DCT coefficient values in described the first coefficient block set, search and remove DCT coefficient value in the first coefficient block set after rounding and be all 0 sub-block, form the second coefficient block set;
The DCT coefficient value of opposite position in described the first coefficient block set and the second coefficient block set is got difference by C, described DCT quantizing noise set generation module, forms the set of DCT quantizing noise;
D, described determination module calculate the variance yields of all coefficient values in the set of described DCT quantizing noise, and this variance yields and default threshold value are compared, if described variance yields is less than threshold value, to look like be JEPG decompressing image to process decision chart.
Described image discriminating method, wherein, also comprises before described steps A: described image type is differentiated with modular converter and judged image type, and in the time that image is RGB coloured image, converted image is YCbCr image.
Described image discriminating method, wherein, described steps A is specially:
Image is divided into the sub-block of nonoverlapping 8 × 8 pixel sizes continuously by A1, described the first coefficient block set generation module, searches and remove that to contain pixel value be 0 or 255 sub-block, and remaining sub-block is obtained converting front set by original sequencing sequence;
A2, described the first coefficient block set generation module carry out respectively dct transform and obtain the first coefficient block set converting in front set sub-block.
Described image discriminating method, wherein, described step B is specially:
B1, described the second coefficient block set generation module by its fractional part rounding operation that rounded up, obtain rounding rear coefficient block set by all DCT coefficient values in described the first coefficient block set;
It is all 0 sub-block that B2, described the second coefficient block set generation module round in rear coefficient block set 2-64 coefficient value described in searching and removing, and residue sub-block forms the second coefficient block set.
Described image discriminating method, wherein, described step C is specially:
C1, described DCT quantizing noise set generation module are compared described the first coefficient block set and described the second coefficient block set, retain sub-block corresponding with described the second coefficient block collection location in described the first coefficient block set and form the 3rd coefficient block set;
The DCT coefficient value of opposite position in described the 3rd coefficient block set and the second coefficient block set is got difference by C2, described DCT quantizing noise set generation module, and all differences are formed to the set of DCT quantizing noise by original sequencing sequence.
Described image discriminating method, wherein, if described variance yields is more than or equal to threshold value in described step D, described determination module process decision chart picture is compressed image not.
Described image discriminating method, wherein, described threshold value is 0.069.
Described image discriminating method, wherein, image is divided into the sub-block of nonoverlapping 8 × 8 pixel sizes continuously by described the first coefficient block set generation module, occurs remainder after cutting apart, and these remainder less than 8 × 8 pixel sizes, remove this remainder.
Beneficial effect: the invention provides a kind of J image discriminating device and method of discrimination thereof, realize by not effective discriminating of compressed image and JEPG decompressing image image dimerous by apparatus of the present invention and method, also can be that unpressed image (such as tiff format, BMP form etc.) determines whether to be contracted by jpeg decompression and saves as the image of current format again to picture format, especially the image with high compression quality that cannot differentiate for prior art, method of the present invention can effectively differentiate whether it is JEPG decompressing image.Image discriminating method of the present invention has more sane performance in the differentiation work of small size (as 32 × 32) image in addition.
Accompanying drawing explanation
Fig. 1 is JEPG image compression process schematic diagram in prior art.
Fig. 2 is JEPG image decompression compression process schematic diagram in prior art.
Fig. 3 is image in prior art
iformation schematic diagram.
Fig. 4 is the theory diagram of image discriminating device in the specific embodiment of the invention.
Fig. 5 is image discriminating method flow chart in the specific embodiment of the invention.
Fig. 6 is the concrete grammar flow chart of step S100 in Fig. 5.
Fig. 7 is that in image discriminating method of the present invention, image is cut apart schematic diagram.
Fig. 8 is that in image discriminating method of the present invention, image is cut apart the schematic diagram that occurs remainder.
Fig. 9 removes sub-block and residue sub-block sequence schematic diagram in image discriminating method of the present invention.
Figure 10 is DCT coefficient value chronological order schematic diagram of the present invention.
Figure 11 is the concrete grammar flow chart of step S300 in Fig. 5.
Figure 12 is the concrete grammar flow chart of step S300 in Fig. 5.
Figure 13 is that in the specific embodiment of the invention, JEPG compression process produces DCT quantizing noise schematic diagram.
Figure 14 is the method flow diagram that in the specific embodiment of the invention, image discriminating device carries out image discriminating.
Figure 15 is image discriminating device image block result schematic diagram in the embodiment of the present invention 1.
Figure 16 is that in the embodiment of the present invention 1, image discriminating device carries out result schematic diagram after dct transform to sub-block.
Figure 17 is that in the embodiment of the present invention 1, image discriminating device rounds sub-block, and removing AC coefficient is 0 sub-block the result schematic diagram that sorts.
Figure 18 is to the discrimination precision result schematic diagram of compressed image and jpeg compressed image not in embodiment 4.
Embodiment
The invention provides a kind of image discriminating device and method of discrimination thereof, for making object of the present invention, technical scheme and effect clearer, clear and definite, below the present invention is described in more detail.Should be appreciated that specific embodiment described herein, only in order to explain the present invention, is not intended to limit the present invention.
A kind of image discriminating device as shown in Figure 4, wherein, described device comprises following part:
The first coefficient block set generation module 100, for image being divided into continuous nonoverlapping sub-block, searching and remove, to contain pixel value be 0 or 255 sub-block, remaining sub-block carried out respectively to dct transform and obtain the first coefficient block set.
The second coefficient block set generation module 200, for all DCT coefficient values of described the first coefficient block set are rounded, searches and removes DCT coefficient value in the first coefficient block set after rounding and be all 0 sub-block, forms the second coefficient block set.
DCT quantizing noise set generation module 300, for the DCT coefficient value of described the first coefficient block set and the second coefficient block set opposite position is got to difference, forms the set of DCT quantizing noise.
In preferred embodiment, described device also comprises:
Image type is differentiated and modular converter 500, and for carrying out the judgement of image type before image discriminating, in the time that image is RGB coloured image, converted image is YCbCr image, and uses luminance component Y.In the time that image is gray-scale map, directly starts the first coefficient block set generation module and carry out corresponding operating.
Be illustrated in figure 5 the image discriminating method of described image discriminating device, wherein, said method comprising the steps of:
Image is divided into continuous nonoverlapping sub-block by S100, described the first coefficient block set generation module, searches and remove that to contain pixel value be 0 or 255 sub-block, remaining sub-block carried out respectively to dct transform and obtain the first coefficient block set.
In preferred embodiment, before described step S100, also comprise: described image type is differentiated with modular converter and judged image type, in the time that image is gray-scale map, directly perform step S100, in the time that image is RGB coloured image, converted image is YCbCr image, uses luminance component Y.
Further, described step S100 as shown in Figure 6, is specially:
Image is divided into the sub-block of nonoverlapping 8 × 8 pixel sizes continuously by S110, described the first coefficient block set generation module, searches and remove that to contain pixel value be 0 or 255 sub-block, and remaining sub-block is obtained converting front set by original sequencing sequence.
Preferably, after cutting apart, there is remainder, and these remainder less than 8 × 8 pixel sizes, remove this remainder.
Concrete processing procedure as shown in Figure 7, by image
ibe divided into continuous nonoverlapping sub-block, each sub-block (for example I
1) size is 8 × 8 pixels.As shown in Figure 8, for finally segmenting sub-block I
2after, remainder P pixel value less than 8 × 8 pixel value sizes, directly remove this P part, statistics institute cuts apart and obtains
individual sub-block.
(
) represent the
individual sub-block, for ease of mark, is described as its sub-block combination
, be the front set of conversion.
Due to image being carried out in the process of jpeg decompression contracting, be less than 0 or be greater than 255 coefficient and all can be truncated into 0 or 255, can produce thus error (or being called truncation noise).For avoiding the truncation noise producing to affect the differentiation performance of the inventive method, incite somebody to action
middle pixel value is 0 or 255 sub-block removal, and remaining sub-block quantity is
,
.The effective sub-block of residue, according to original sequencing rearrangement, is obtained
, as shown in Figure 9, for example, suppose to contain in sub-block 5 255 pixels.In sub-block 7, contain 0 pixel, sub-block 5 and sub-block 7 are deleted, remaining sub-block is resequenced according to original order.
S120, described the first coefficient block set generation module carry out respectively dct transform and obtain the first coefficient block set converting in front set sub-block.
Concrete, before described conversion, set is
(
), right respectively
(
) implement dct transform, obtain the first coefficient block set
, wherein,
represent piece index value,
represent frequency indices value,
represent the
in individual sub-block
individual coefficient value, wherein, when
time,
represent DC coefficient (DC) value, when
,
represent ac coefficient (AC) value.DCT coefficient value coded sequence as shown in figure 10, carries out coefficient value layout to 8 × 8 coefficient value pieces (as form 10) after dct transform, adopts "the" shape sequential organization coefficient value, from the upper left corner, finishes to the lower right corner.Form layout pixel value table as shown in Table 20, the numerical value in table
m(
m=0,1,2 ..., 63), represent respectively after layout
mindividual pixel value, wherein, No. 0 element represents direct current (DC) coefficient after dct transform, all the other 63 element representations exchange (AC) coefficient.In Figure 10, numbering is m value from 0 ~ 63(), actual corresponding order is the from the 1st to the 64th, namely No. 0 corresponding the 1st coefficient of element, No. 1 corresponding the 2nd coefficient of element ... No. 63 corresponding the 64th coefficients of element.
S200, described the second coefficient block set generation module round all DCT coefficient values in described the first coefficient block set, search and remove DCT coefficient value in the first coefficient block set after rounding and be all 0 sub-block, form the second coefficient block set.
In preferred embodiment, described step S200 as shown in figure 11, is specially:
S210, described the second coefficient block set generation module by its fractional part rounding operation that rounded up, obtain rounding rear coefficient block set by all DCT coefficient values in described the first coefficient block set.To described
(
) in the fractional part round computing of all DCT coefficient value.Obtaining new coefficient value piece is
.
It is all 0 sub-block that S220, described the second coefficient block set generation module round in rear coefficient block set 2-64 coefficient value described in searching and removing, and residue sub-block forms the second coefficient block set.Inspect one by one above-mentioned [
], be that zero sub-block is removed (remove ac coefficient value be entirely 0 sub-block) entirely by 2-64 coefficient.Remaining sub-block quantity is
, obtain
, as shown in figure 10, be that 0 sub-block is removed entirely by being numbered 1-63 element (2-64 coefficient in corresponding sub-block) in table 20.
The DCT coefficient value of opposite position in described the first coefficient block set and the second coefficient block set is got difference by S300, described DCT quantizing noise set generation module, forms the set of DCT quantizing noise.
In preferred embodiment, described step S300 as shown in figure 12, is specially:
S310, described DCT quantizing noise set generation module are compared described the first coefficient block set and described the second coefficient block set, retain sub-block corresponding with described the second coefficient block collection location in described the first coefficient block set and form the 3rd coefficient block set.Utilize effective sub-block.To the set obtaining in described step S120
process, only in reservation and described step S220, obtain [
] in corresponding that in position
individual sub-block, obtains new coefficient value piece
, be the 3rd coefficient block set.
The DCT coefficient value of opposite position in described the 3rd coefficient block set and the second coefficient block set is got difference by S320, described DCT quantizing noise set generation module, and all differences are formed to the set of DCT quantizing noise by original sequencing sequence.As shown in figure 13, compressed image 30 is not processed according to compression method of the present invention (according to method described in S100, S200 step), in quantizing process, right
[
] coefficient of opposite position is got difference between the two, can obtain DCT quantizing noise
, wherein
, (
).Comprised thus
the difference of all coefficient of correspondence in individual sub-block, altogether
× 64 elements, this
individual sub-block, by original order sequence, obtains
, be the set of DCT quantizing noise.
S400, described determination module calculate the variance yields of all coefficient values in the set of described DCT quantizing noise, and this variance yields and default threshold value are compared, if described variance yields is less than threshold value, to look like be JEPG decompressing image to process decision chart.
And described variance yields is more than or equal to threshold value, described determination module process decision chart picture is compressed image not.
In preferred embodiment, described threshold value is 0.069.
Concrete, to above-mentioned
in the coefficient value of all sub-blocks, all its quantizing noises of DCT coefficient are got variance.First all DCT quantizing noises are got to average, obtain
, then can obtain variance yields
; Set a threshold value
, when the variance drawing
be more than or equal to this threshold value
, judge that given test pattern is compressed image not, otherwise, be jpeg decompression contract drawing picture.?
.
The specific embodiment that carries out as shown in figure 14 image discriminating for image discriminating device of the present invention, concrete steps are as follows:
H1, Given Graph picture
i, be divided into nonoverlapping 8 × 8 sub-block of pixels continuously.
H2, removal
iin to contain pixel value be 0 or 255 sub-block.
H3, piecemeal are implemented dct transform, and after removal conversion, AC coefficient is zero sub-block entirely.
H4, corresponding coefficient value is got to difference, obtain the set of DCT coefficient quantization noise
n
H5, right
nin all coefficient values get variance.
H6、
≥
？。If
be more than or equal to
, process decision chart picture
icompressed image not, otherwise,
iit is jpeg decompression contract drawing picture.
Below by embodiment, image discriminating device of the present invention and method of discrimination thereof are further described.
Do not compress the coloured image of tiff format one of UCID image library random choose.
The first coefficient block set generation module of described image discriminating device intercepts into selected image 32 × 32 image block from central authorities.Carry out 8 × 8 piecemeals, be divided into 16 sub-blocks, as shown in figure 15.Find the 8th, 12 sub-blocks and contain pixel value 255, after the 8th, 12 sub-blocks are removed, remaining 14 sub-blocks sort by original sequencing, then carry out dct transform, obtain DCT coefficient value, as shown in figure 16.
Described the second coefficient block set generation module carries out rounding operation to sub-block as shown in figure 16, removes the sub-block that in acquired results, all AC coefficients are zero, and rearrangement, obtains result as shown in figure 17.
Described DCT quantizing noise set generation module is to getting difference between the effective sub-block shown in Figure 17, and passes through described determination module and calculate variance, obtains variance yields and is
.By this value and described threshold value
(0.069) compare, obtain the result that this variance yields is greater than threshold value, therefore show that image is the result of determination of compressed image not.Result of determination is correct.
By the random coloured image of downloading a jpeg format in the Internet, again carry out according to step described in embodiment 1.
First differentiate with modular converter this jpeg image preservation form is tiff image and tiff image is turned to gray value by described image type, described the first coefficient block set generation module does not find the sub-block containing 0 or 255 pixel values after to this image block, all sub-blocks are carried out to dct transform
Described the second coefficient block set generation module is processed the sub-block after converting, and the sub-block 1,6,7,12,13,14 that is not zero entirely by ac coefficient retains and resequences.
Described DCT quantizing noise set generation module is got difference to the DCT coefficient value between the sub-block after sorting, and calculates variance by described discrimination module, obtains variance yields and is
and compare with described threshold value, because be less than threshold value
so it is jpeg decompression contract drawing picture that process decision chart looks like.Result of determination is correct.
Go to JPEG and go back to again uncompressed form image discriminating device and method of the present invention is verified not compress.
In UCID image library, select at random two tiff format image TIF1 and TIF2, be compressed into jpeg image JPG1 and JPG2 with compressibility factor Q=99 and Q=100 respectively;
By JPG1 and JPG2 respectively solution push back tiff format image, preserve also and check according to the step described in embodiment 1.Obtaining final result is:
The variance yields of TIF1
, be less than threshold value
, therefore image is jpeg decompression contract drawing picture.Result of determination is correct.
The variance yields of TIF2
, be less than threshold value
, therefore image is jpeg decompression contract drawing picture.Result of determination is correct.
Utilize 2500 not compressed image come image discriminating device and method of the present invention test.Be translated into gray-scale map, and intercept middle body and generate the image of smaller szie, if pixel is 256 × 256,128 × 128,64 × 64,32 × 32 image.Then with compressibility factor QF=100,99,98,85,75 and 50, it is compressed respectively, then utilize image discriminating device of the present invention to differentiate it.Method (the W. Luo that simultaneously utilizes the people such as Weiqi Luo to propose, J. Huang, and G. Qiu, " JPEG error analysis and its applications to Digital Image Forensics " IEEE Trans. Inf. Forensics Security, vol. 5, no. 3, pp. 480-491, 2010) as a comparison, ratio of precision between the two is to as shown in 18, as can be seen from the figure, in the time of QF=100 and 99, i.e. in the situation that quantization step is little (being that step-length is 1 or 2), utilize the huge lifting that has that the people such as differentiation result ratio of precision Luo that image discriminating device of the present invention and method of discrimination thereof obtain propose.
The invention provides a kind of image discriminating device and method of discrimination thereof, realize by not effective discriminating of compressed image and JEPG decompressing image image dimerous by apparatus of the present invention and method, especially the image with high compression quality that cannot differentiate for prior art, method of the present invention can effectively differentiate whether it is JEPG decompressing image.Image discriminating method of the present invention has more sane performance in the differentiation work of small size (as 32 × 32) image in addition.
Should be understood that, application of the present invention is not limited to above-mentioned giving an example, and for those of ordinary skills, can be improved according to the above description or convert, and all these improvement and conversion all should belong to the protection range of claims of the present invention.
Claims (10)
1. an image discriminating device, is characterized in that, described device comprises following part:
The first coefficient block set generation module, for image being divided into continuous nonoverlapping sub-block, searching and remove, to contain pixel value be 0 or 255 sub-block, remaining sub-block carried out respectively to dct transform and obtain the first coefficient block set;
The second coefficient block set generation module, for all DCT coefficient values of described the first coefficient block set are rounded, searches and removes DCT coefficient value in the first coefficient block set after rounding and be all 0 sub-block, forms the second coefficient block set;
DCT quantizing noise set generation module, for the DCT coefficient value of described the first coefficient block set and the second coefficient block set opposite position is got to difference, forms the set of DCT quantizing noise;
Determination module, for calculating the variance yields of all coefficient values of described DCT quantizing noise set, compares this variance yields and default threshold value, if described variance yields is less than threshold value, to look like be JEPG decompressing image to process decision chart.
2. image discriminating device according to claim 1, is characterized in that, described device also comprises:
Image type is differentiated and modular converter, and for carrying out the judgement of image type before image discriminating, in the time that image is RGB coloured image, converted image is YCbCr image.
3. an image discriminating method that utilizes image discriminating device as claimed in claim 1 to carry out, is characterized in that, said method comprising the steps of:
Image is divided into continuous nonoverlapping sub-block by A, described the first coefficient block set generation module, searches and remove that to contain pixel value be 0 or 255 sub-block, remaining sub-block carried out respectively to dct transform and obtain the first coefficient block set;
B, described the second coefficient block set generation module round all DCT coefficient values in described the first coefficient block set, search and remove DCT coefficient value in the first coefficient block set after rounding and be all 0 sub-block, form the second coefficient block set;
The DCT coefficient value of opposite position in described the first coefficient block set and the second coefficient block set is got difference by C, described DCT quantizing noise set generation module, forms the set of DCT quantizing noise;
D, described determination module calculate the variance yields of all coefficient values in the set of described DCT quantizing noise, and this variance yields and default threshold value are compared, if described variance yields is less than threshold value, to look like be JEPG decompressing image to process decision chart.
4. image discriminating method according to claim 3, is characterized in that, before described steps A, also comprises: described image type is differentiated with modular converter and judged image type, and in the time that image is RGB coloured image, converted image is YCbCr image.
5. image discriminating method according to claim 3, is characterized in that, described steps A is specially:
Image is divided into the sub-block of nonoverlapping 8 × 8 pixel sizes continuously by A1, described the first coefficient block set generation module, searches and remove that to contain pixel value be 0 or 255 sub-block, and remaining sub-block is obtained converting front set by original sequencing sequence;
A2, described the first coefficient block set generation module carry out respectively dct transform and obtain the first coefficient block set converting in front set sub-block.
6. image discriminating method according to claim 3, is characterized in that, described step B is specially:
B1, described the second coefficient block set generation module by its fractional part rounding operation that rounded up, obtain rounding rear coefficient block set by all DCT coefficient values in described the first coefficient block set;
It is all 0 sub-block that B2, described the second coefficient block set generation module round in rear coefficient block set 2-64 coefficient value described in searching and removing, and residue sub-block forms the second coefficient block set.
7. image discriminating method according to claim 3, is characterized in that, described step C is specially:
C1, described DCT quantizing noise set generation module are compared described the first coefficient block set and described the second coefficient block set, retain sub-block corresponding with described the second coefficient block collection location in described the first coefficient block set and form the 3rd coefficient block set;
The DCT coefficient value of opposite position in described the 3rd coefficient block set and the second coefficient block set is got difference by C2, described DCT quantizing noise set generation module, and all differences are formed to the set of DCT quantizing noise by original sequencing sequence.
8. image discriminating method according to claim 3, is characterized in that, if described variance yields is more than or equal to threshold value in described step D, described determination module process decision chart picture is compressed image not.
9. image discriminating method according to claim 3, is characterized in that, described threshold value is 0.069.
10. image discriminating method according to claim 5, it is characterized in that, image is divided into the sub-block of nonoverlapping 8 × 8 pixel sizes continuously by described the first coefficient block set generation module, after cutting apart, there is remainder, and these remainder less than 8 × 8 pixel sizes, remove this remainder.
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| CN108230411A (en) * | 2017-12-29 | 2018-06-29 | 成都工业学院 | The detection method and device of a kind of tampered image |
| CN115170779A (en) * | 2022-07-18 | 2022-10-11 | 生态环境部环境规划院 | Remote sensing image rendering and network publishing method |
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| CN103067713A (en) * | 2013-01-06 | 2013-04-24 | 中国科学院深圳先进技术研究院 | Method and system of bitmap joint photographic experts group (JPEG) compression detection |
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| CN107680386A (en) * | 2017-11-07 | 2018-02-09 | 潘柏霖 | A kind of intelligent traffic monitoring system |
| CN108230411A (en) * | 2017-12-29 | 2018-06-29 | 成都工业学院 | The detection method and device of a kind of tampered image |
| CN108230411B (en) * | 2017-12-29 | 2021-03-09 | 成都工业学院 | Method and device for detecting tampered image |
| CN115170779A (en) * | 2022-07-18 | 2022-10-11 | 生态环境部环境规划院 | Remote sensing image rendering and network publishing method |
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