CN111327905B - Preprocessing method and system for realizing similar image compression based on FPGA - Google Patents
Preprocessing method and system for realizing similar image compression based on FPGA Download PDFInfo
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Abstract
The invention provides a preprocessing method and a preprocessing system for realizing similar image compression based on an FPGA (field programmable gate array), belonging to the technical field of image processing, wherein the method receives a plurality of similar images by utilizing an external FPGA chip; calculating the average value or the median of data of pixel points at the same position in a plurality of similar images to form a model image; comparing each similar image with the model image respectively, and calculating the absolute value of the difference value of the data of the pixel points at the same position; if the absolute value of the difference value corresponding to more than two continuous pixel points is less than or equal to a preset model threshold, outputting the position information of the first pixel point and the quantity information of the continuous pixel points; if not, outputting the original image data. The invention utilizes the external FPGA chip to process, has high compression ratio and short compression time, can release the computer to perform other processing, and can further compress the compressed data by using the traditional compression method to improve the compression ratio of the image.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a preprocessing method and a preprocessing system for realizing similar image compression based on an FPGA (field programmable gate array).
Background
The biggest disadvantage of the conventional compression is that it is based on the image itself, so when a plurality of similar images are compressed, the conventional compression algorithm needs to compress each image separately, and this results in low compression rate and long compression time of the image. Moreover, when a large number of similar images are compressed, a large amount of compression time and memory space of a computer are occupied, and CPU resources are wasted.
Disclosure of Invention
The invention aims to provide a preprocessing method and a preprocessing system for realizing similar image compression based on an FPGA (field programmable gate array), and solves the problems of low compression ratio, long compression time and occupation of a computer CPU (central processing unit) and an internal memory when similar images are compressed by a traditional compression method.
In order to solve the technical problem, the invention provides a preprocessing method for realizing similar image compression based on an FPGA (field programmable gate array), which comprises the following steps of:
s1, receiving a plurality of similar images by the FPGA chip;
s3, calculating the average value or the median of the data of the pixel points at the same position in the multiple similar images to form a model image;
s4, comparing each similar image with the model image respectively, and calculating the absolute value of the difference value of the data of the pixel points at the same position;
s5, if the absolute value of the difference value corresponding to more than two continuous pixel points is less than or equal to the preset model threshold, outputting the position information of the first pixel point and the quantity information of the continuous pixel points; if not, outputting the original image data.
Further, the steps between the steps S1 and S3 further include the steps of:
s2, after receiving a plurality of similar images, calculating the image similarity among the similar images, and dividing the similar images into a plurality of groups according to the image similarity; model images of a plurality of similar images in each group are calculated, and steps S4 and S5 are respectively executed on each group of similar images.
Further, the grouping in step S2 specifically includes:
s21, taking the first image as a reference image and marking a packet sequence number;
s22, calculating the image similarity between the next image and the current reference image, and marking the currently calculated image with the same grouping serial number as the current reference image if the similarity meets a preset threshold; if the similarity does not meet the preset threshold value, taking the currently calculated image as a new reference image and marking a new grouping serial number;
and S23, repeating the step S22 until the last image is also marked with the grouping sequence number, and dividing all images marked with the same grouping sequence number into a group.
Further, the image similarity is calculated by a structural similarity measure, a cosine similarity or histogram matching.
Further, step S4 is specifically: and dividing the similar image and the corresponding model image into a plurality of blocks, comparing the blocks in parallel, and calculating the absolute value of the difference value of the data of the pixel points at the same position.
Further, the pretreatment method further comprises the steps of:
and S6, packaging and outputting the comparison result of the step S5, specifically outputting the model image as it is, outputting the position information and the number information according to a length plus distance format, and outputting the original image data of the rest pixels according to a length plus character format.
The invention also provides a preprocessing system for realizing similar image compression by using the preprocessing method for realizing similar image compression based on the FPGA, which comprises the following steps:
an image receiving module: for receiving a plurality of similar images;
an image modeling module: calculating the average value or the median of data of pixel points at the same position in a plurality of similar images to form a model image;
an image comparison module: comparing each similar image with the model image respectively, and calculating the absolute value of the difference value of the data of the pixel points at the same position; if the absolute value of the difference value corresponding to more than two continuous pixel points is less than or equal to a preset model threshold, outputting the position information of the first pixel point and the quantity information of the continuous pixel points; if not, outputting the original image data.
The image grouping module is used for calculating the image similarity among a plurality of similar images after receiving the similar images and dividing the similar images into a plurality of groups according to the image similarity; the image modeling module is also used for calculating model images of a plurality of similar images in each group.
Further, the data packaging module is used for packaging and outputting the model image and the comparison result of each similar image and the model image.
Further, an external memory module is included for storing model images of the sets of similar images.
The invention has the beneficial effects that: the method comprises the steps of receiving a plurality of similar images by using an external FPGA, and calculating the average value or the median of data of pixel points at the same position in the plurality of similar images to obtain a model image; comparing each similar image with the model image, and comparing with a model threshold value, because the similarity of information between the similar images is very large, the data of pixels which are close to the model image in each similar image can be replaced by the data of the model image, thereby simplifying the data of a large number of close and continuous pixels into two data: the compression rate is greatly improved due to the position information and the quantity information; meanwhile, the process is processed by using an external FPGA device, so that the operation rate can be improved, and the memory and the CPU of the computer can be released for other processing; and the data after being preprocessed by the method can be further compressed by a traditional compression method.
Furthermore, the similar images are grouped by calculating the image similarity among the similar images, so that each similar image in each group has extremely high similarity with the model image of the group, and the compression ratio of the similar images can be improved; or the grouping threshold is adjusted up to reduce the loss of image data.
Furthermore, before the absolute value of the difference value of the pixel point data is calculated, the similar image and the corresponding model image are divided into a plurality of blocks, and each block is compared in parallel, so that the processing efficiency is improved, and the compression time is shortened.
Each module of the system can be subjected to parallel pipelining processing, so that the processing efficiency is improved; the interface between the modules is simple, the data flow direction is clear, and the realization is easy; the model images are stored in the external memory module, and the corresponding model images are called when image comparison is carried out, so that the occupied storage space of the FPGA can be reduced, and the compression rate is improved.
Drawings
FIG. 1 is a flow chart of a preprocessing method for implementing similar image compression based on FPGA according to the present invention;
FIG. 2 is a schematic packaging diagram of a preprocessing method for implementing similar image compression based on FPGA according to the present invention;
FIG. 3 is a flow chart of a pre-processing method for similar image compression of image packets according to the present invention;
FIG. 4 is a flowchart of image grouping of a preprocessing method for implementing similar image compression based on FPGA according to the present invention;
FIG. 5 is a block diagram of a preprocessing system for implementing similar image compression based on FPGA according to the present invention.
Detailed Description
The invention will be further described with reference to the accompanying drawings in which:
the method comprises the steps of receiving a plurality of similar images by using an external FPGA, and calculating the average value or the median of data of pixel points at the same position in the plurality of similar images to obtain a model image; comparing each similar image with the model image, and comparing with a model threshold value, because the similarity of information between the similar images is very large, the data of pixels which are close to the model image in each similar image can be replaced by the data of the model image, thereby simplifying the data of a large number of close and continuous pixels into two data: the compression rate is greatly improved due to the position information and the quantity information; meanwhile, the process is processed by using an external FPGA device, so that the operation rate can be improved, and the memory and the CPU of the computer can be released for other processing; and the data after being preprocessed by the method can be further compressed by a traditional compression method.
The invention discloses a preprocessing method for realizing similar image compression based on FPGA (field programmable gate array), which comprises the following steps as shown in figure 1:
s1, receiving a plurality of similar images by the FPGA chip;
s3, calculating the average value or the median of the data of the pixel points at the same position in the multiple similar images to form a model image;
s4, comparing each similar image with the model image respectively, and calculating the absolute value of the difference value of the data of the pixel points at the same position;
s5, if the absolute value of the difference value corresponding to more than two continuous pixel points is less than or equal to the preset model threshold, outputting the position information of the first pixel point and the quantity information of the continuous pixel points; if not, outputting the original image data.
In the present invention, the average value or the median may be calculated accordingly according to the type of the image. For example, if the received similar images are in a color RGB format, the average value or the median of the data of the pixel points at the same position in the plurality of similar images is calculated by the channel, that is, three times, and the model image of each channel is formed, and S3 and S4 are also compared by the channel. The CMYK mode is divided into four channels. If the received similar image is a gray scale image, calculation is directly carried out without channel division. The calculation of the mean or median is also applicable to the following method embodiments and systems.
The model threshold in step S5 can be adjusted according to the degree of demand for the final result, and is reasonably adjusted between the compression rate and the image loss rate.
Further, step S4 is specifically: and dividing the similar image and the corresponding model image into a plurality of blocks, comparing the blocks in parallel, calculating the absolute value of the difference value of the data of the pixel points at the same position, improving the efficiency of calculating the difference value by utilizing the parallel processing capacity of the FPGA chip and reducing the compression processing time.
Further, the pretreatment method further comprises the steps of:
s6, packaging and outputting the comparison result of step S5, as shown in fig. 2, specifically outputting the model image as it is, outputting the position information and the number information in a format of length plus distance, and outputting the original image data of the remaining pixels in a format of length plus character. To distinguish the data types, each type of data is preceded by 2 bits indicating the data type: 00 denotes model image data, 01 denotes data of two or more continuous pixels satisfying a preset model threshold in each similar image, 10 denotes a data portion of the remaining pixels in each similar image, and 11 denotes end. The data type is followed by a length field for indicating length information and quantity information of each part; the distance field indicates the starting position of the same data portion in each similar image in the model image, and the distance field only appears in data blocks of type 01.
The invention also discloses another preprocessing method for realizing similar image compression based on FPGA, as shown in FIG. 3, comprising:
s1, receiving a plurality of similar images by the FPGA chip;
s2, calculating the image similarity among the similar images, and dividing the similar images into a plurality of groups according to the image similarity;
s3', calculating the average value or the median of the data of the pixel points at the same position in the plurality of similar images in each group to form a model image;
s4', each similar image in each group is compared with the corresponding model image, and the absolute value of the difference value of the data of the pixel points at the same position is calculated;
s5, if the absolute value of the difference value corresponding to more than two continuous pixel points is less than or equal to the preset model threshold, outputting the position information of the first pixel point and the quantity information of the continuous pixel points; if not, outputting the original image data.
The method for dividing a plurality of similar images into a plurality of groups comprises the following steps:
s21, taking the first image as a reference image and marking a packet sequence number;
s22, calculating the image similarity between the next image and the current reference image, and marking the currently calculated image with the same grouping serial number as the current reference image if the similarity meets a preset threshold; if the similarity does not meet the preset threshold value, taking the currently calculated image as a new reference image and marking a new grouping serial number; the threshold value of the step can be flexibly adjusted according to the requirements of the image data.
And S23, repeating the step S22 until the last image is also marked with the grouping sequence number, and dividing all images marked with the same grouping sequence number into a group. The marked grouping sequence number is convenient for later identification during image modeling, and then the grouped images are output to the modeling module.
Fig. 4 shows a flow chart of the method, which stops when the last image is calculated.
Further, the image similarity is calculated through structural similarity measurement, cosine similarity or histogram matching and the like, and images with high similarity are divided into a group through the image similarity.
Further, the method of the previous method of dividing the similar image and the corresponding model image into a plurality of blocks and outputting the package of the comparison result is also applicable to the present method.
The two preprocessing methods for similar image compression have no complex compression algorithm, do not need repeated iterative operation of data, and greatly shorten the compression time; the compression method is simple and easy to realize; meanwhile, FPGA pipeline processing is adopted, so that the operation speed is further increased, and the compression time is saved. After compression is complete, the image may be retransmitted to a computer or other device.
The present invention further provides a similar image compression preprocessing system for implementing the above preprocessing method for implementing similar image compression based on FPGA, as shown in fig. 5, including:
the image receiving module 201: for receiving a plurality of similar images;
the image modeling module 203: calculating the average value or the median of data of pixel points at the same position in a plurality of similar images to form a model image;
the image comparison module 204: comparing each similar image with the model image respectively, and calculating the absolute value of the difference value of the data of the pixel points at the same position; if the absolute value of the difference value corresponding to more than two continuous pixel points is less than or equal to a preset model threshold, outputting the position information of the first pixel point and the quantity information of the continuous pixel points; if not, outputting the original image data.
Further, the image grouping module 202 is further included, configured to calculate an image similarity between the multiple similar images after receiving the multiple similar images, and divide the multiple similar images into a plurality of groups; then the image modeling module is used for calculating model images of a plurality of similar images in each group; and the image comparison module compares each similar image in each group with the model image of the group respectively to obtain a comparison result of each similar image.
Further, a data packaging module 205 is further included for packaging and outputting the model image and the comparison result of each similar image and the model image.
Further, an external memory 206 is included for storing the image model and outputting a corresponding model image according to the query request of the image comparison module. And the corresponding model image is called when the images are compared, so that the memory of the FPGA can be greatly saved.
Each module can be subjected to parallel pipelining processing, so that the processing efficiency is improved; the interface between the modules is simple, the data flow direction is clear, and the realization is easy; and an external memory is adopted, so that the memory space of the CPU is saved.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A preprocessing method for realizing similar image compression based on FPGA is characterized by comprising the following steps:
s1, receiving a plurality of similar images by the FPGA chip;
s3, calculating the average value or the median of the data of the pixel points at the same position in the multiple similar images to form a model image;
s4, comparing each similar image with the model image respectively, and calculating the absolute value of the difference value of the data of the pixel points at the same position;
s5, if the absolute value of the difference value corresponding to more than two continuous pixel points is less than or equal to the preset model threshold, outputting the position information of the first pixel point and the quantity information of the continuous pixel points; if not, outputting the original image data.
2. The preprocessing method for realizing similar image compression based on FPGA according to claim 1, further comprising the steps between S1 and S3:
s2, after receiving a plurality of similar images, calculating the image similarity among the similar images, and dividing the similar images into a plurality of groups according to the image similarity; model images of a plurality of similar images in each group are calculated, and steps S4 and S5 are respectively executed on each group of similar images.
3. The preprocessing method for realizing similar image compression based on FPGA of claim 2, wherein the grouping in step S2 specifically includes:
s21, taking the first image as a reference image and marking a packet sequence number;
s22, calculating the image similarity between the next image and the current reference image, and marking the currently calculated image with the same grouping serial number as the current reference image if the similarity meets a preset threshold; if the similarity does not meet the preset threshold value, taking the currently calculated image as a new reference image and marking a new grouping serial number;
and S23, repeating the step S22 until the last image is also marked with the grouping sequence number, and dividing all images marked with the same grouping sequence number into a group.
4. The preprocessing method for realizing similar image compression based on FPGA of claim 2, wherein the image similarity is calculated by structural similarity measurement, cosine similarity or histogram matching.
5. The preprocessing method for realizing similar image compression based on the FPGA according to any one of claims 1 to 4, wherein the step S4 specifically comprises: and dividing the similar image and the corresponding model image into a plurality of blocks, comparing the blocks in parallel, and calculating the absolute value of the difference value of the data of the pixel points at the same position.
6. The preprocessing method for realizing similar image compression based on the FPGA according to any one of claims 1 to 4, characterized in that the preprocessing method further comprises the steps of:
and S6, packaging and outputting the comparison result of the step S5, specifically outputting the model image as it is, outputting the position information and the number information according to a length plus distance format, and outputting the original image data of the rest pixels according to a length plus character format.
7. A pre-processing system for similar image compression for implementing the pre-processing method for implementing similar image compression based on FPGA of claim 1, comprising:
an image receiving module: for receiving a plurality of similar images;
an image modeling module: the method comprises the steps of calculating the average value or the median of data of pixel points at the same position in a plurality of similar images to form a model image;
an image comparison module: the model image processing device is used for comparing each similar image with the model image respectively and calculating the absolute value of the difference value of the data of the pixel points at the same position; if the absolute value of the difference value corresponding to more than two continuous pixel points is less than or equal to a preset model threshold, outputting the position information of the first pixel point and the quantity information of the continuous pixel points; if not, outputting the original image data.
8. The preprocessing system for realizing similar image compression based on FPGA of claim 7, further comprising an image grouping module for calculating image similarity among a plurality of similar images after receiving the plurality of similar images and dividing the similar images into a plurality of groups according to the image similarity; the image modeling module is also used for calculating model images of a plurality of similar images in each group.
9. The preprocessing system for realizing similar image compression based on FPGA according to claim 7 or 8, characterized by further comprising a data packaging module for packaging and outputting the model image and the comparison result of each similar image and the model image.
10. The pre-processing system for realizing similar image compression based on FPGA as claimed in claim 7, further comprising an external memory module for storing model images of each group of similar images.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012043397A (en) * | 2010-07-21 | 2012-03-01 | Nippon Telegr & Teleph Corp <Ntt> | Feature amount acquisition device, feature amount acquisition method, similar image retrieval method and program |
| CN103077499A (en) * | 2013-01-09 | 2013-05-01 | 西安电子科技大学 | SAR (Synthetic Aperture Radar) image pre-processing method based on similar block |
| CN104869425A (en) * | 2015-05-13 | 2015-08-26 | 信阳师范学院 | Compression and decompression method based on texture image similarity |
| CN105407353A (en) * | 2014-09-11 | 2016-03-16 | 腾讯科技（深圳）有限公司 | Image compression method and apparatus |
| CN106231214A (en) * | 2016-08-11 | 2016-12-14 | 复旦大学 | High-speed cmos sensor image based on adjustable macro block approximation lossless compression method |
| CN106326908A (en) * | 2015-06-30 | 2017-01-11 | 中兴通讯股份有限公司 | Picture management method and apparatus, and terminal equipment |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP6689508B2 (en) * | 2016-04-12 | 2020-04-28 | シナプティクス・ジャパン合同会社 | Image processing device, compression circuit, display driver, display device, and image processing method |
-
2020
- 2020-01-09 CN CN202010022226.7A patent/CN111327905B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012043397A (en) * | 2010-07-21 | 2012-03-01 | Nippon Telegr & Teleph Corp <Ntt> | Feature amount acquisition device, feature amount acquisition method, similar image retrieval method and program |
| CN103077499A (en) * | 2013-01-09 | 2013-05-01 | 西安电子科技大学 | SAR (Synthetic Aperture Radar) image pre-processing method based on similar block |
| CN105407353A (en) * | 2014-09-11 | 2016-03-16 | 腾讯科技（深圳）有限公司 | Image compression method and apparatus |
| CN104869425A (en) * | 2015-05-13 | 2015-08-26 | 信阳师范学院 | Compression and decompression method based on texture image similarity |
| CN106326908A (en) * | 2015-06-30 | 2017-01-11 | 中兴通讯股份有限公司 | Picture management method and apparatus, and terminal equipment |
| CN106231214A (en) * | 2016-08-11 | 2016-12-14 | 复旦大学 | High-speed cmos sensor image based on adjustable macro block approximation lossless compression method |
Non-Patent Citations (2)
| Title |
|---|
| Shaou-Gang Miaou ; Fu-Sheng Ke ; Shu-Ching Chen.A Lossless Compression Method for Medical Image Sequences Using JPEG-LS and Interframe Coding.《 IEEE Transactions on Information Technology in Biomedicine》.2009, * |
| 无人机侦察图像压缩;王源源，黄大庆;《光学精密工程》;20140515;全文 * |
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