Integrative compressing method and device of image

A compression method, image technology, applied in the direction of image communication, television, electrical components, etc.

Inactive Publication Date: 2011-06-15
TONGJI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0027] However, many of the above-mentioned technologies have many

Method used

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  • Integrative compressing method and device of image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0097] H.264 with fixed quantization factor is used to perform lossy encoding, lossless compression uses dictionary compression gzip, Hextile encoding in remote frame buffer RFB (remote frame buffer) protocol; ZRLE encoding in remote frame buffer RFB (remote frame buffer) protocol Some encoding methods in , specifically refer to all encoding methods that appear before the zlib encoding step, we call it RLE (Run-Length Encoding) encoding; and four filtering methods in PNG (Portable Network Graphics). Each pixel uses n-bits R, G, B (red, green, blue) for a total of 3n-bit RGB representation.

[0098] An integrated encoding method for images, the process is as follows Figure 7 shown, including:

[0099] 1. Divide the input image into 16×16 non-overlapping macroblocks, and then repeat steps 2 to 5 for these macroblocks until the last macroblock in the image.

[0100] 2. H.264 and four lossless methods are used for encoding, and each method is encoded once.

[0101] In the spec...

Embodiment 2

[0139] The difference between this embodiment and Embodiment 1 is that: H.264 with a fixed target bit rate and variable quantization factor is used to perform lossy encoding, and lossless compression uses two methods in Embodiment 1: gzip encoding and PRLEG, The encoding process and decoding process of the PRLEG method are as follows Figure 10 and Figure 13 shown. Each pixel uses n-bit Y, Cb, Cr for a total of 3n-bit YUV444 representation. Similar to Embodiment 1, for each coding block, H.264 and two lossless methods are used for coding, and the one with the smallest R-D cost function value is selected as the best coding method. The difference from Embodiment 1 is that for H.264 encoding, after the encoding of the current macroblock is completed, the quantization factor used for the next macroblock needs to be determined according to the preset target number of bits instead of using a fixed quantization factor.

Embodiment 3

[0141] The difference between this embodiment and Embodiment 1 is that: VC-1 with a fixed quantization factor is used to perform lossy encoding, and lossless compression uses gzip encoding. Each pixel uses an average 16-bit YUV422 representation. Similar to Embodiment 1, for each coding block, VC-1 and gzip coding are used, and the one with the smallest R-D cost function value is selected as the best coding method. Different from Embodiment 1, since only one lossless method is used, in the decoding process, there is no need to determine whether the best encoding method of the current encoding block is a lossless method, and to update the dictionary of other lossless methods; similarly Reasonably, the dictionary data update module is not needed in the decoding device.

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Abstract

The invention provides an integrative compressing method and device of an image. The integrative compressing method comprises at least one lossless encoding method and at least one loss encoding method. A basic encoding unit is an encoding sub-block with fixed size. For each encoding sub-block, both loss and lossless encoding methods are used for encoding the encoding sub-blocks for one time, saving encoding results with least R-D (Rate-Distortion) cost function values and marking the corresponding encoding method as an optimal encoding method. In the whole compression process, partial lossless compression and partial loss compression are carried out with ultrahigh image quality. For the lossless encoding which carries out compression by using a dictionary, the data in the dictionary is from N-byte data which is encoded by using the lossless method recently, and the traditional image compression method is only suitable for some image content. Through combining the plurality of lossless and loss encoding methods, for different image contents, the proper encoding method is selected from the view of acquiring the optimal encoding R-D performance, thereby the invention is suitable for compressing the image including the plurality of contents.

Description

technical field [0001] The invention relates to the compression problem of digital images, in particular to the compression problem of composite images including characters, graphics, backgrounds and natural images. Background technique [0002] With the development of computer technology and network technology, the content of digital images is becoming more and more diverse, and composite images including text, graphics, backgrounds and natural images can be seen everywhere. Such as computer screen images, web pages, slides, scanned electronic documents and posters, etc. Compression of composite images is essential in many applications. For example, larger scanned electronic documents are often compressed before storage and distribution. In traditional applications such as computer remote control and distance teaching, as well as new applications such as cloud computing and cloud chip-screen computing, the compression and decompression of computer screen images is a key t...

Claims

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Application Information

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IPC IPC(8): H04N7/26H03M7/40H04N19/147H04N19/176
Inventor 王淑慧林涛
Owner TONGJI UNIV
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