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Coding optimization method and coding optimization device for images

An encoding device and a technology of an encoding method are applied in the field of image optimization encoding method and image optimization encoding device, which can solve the problems of indistinguishable, inability to obtain effects, and image degradation, and achieve the effect of small data amount and good image quality.

Inactive Publication Date: 2010-07-21
GUANGDONG VTRON TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, in some applications, it is impossible to clearly distinguish between the above two situations. For example, when using a computer desktop while browsing photos or watching videos, using either of the above two encoding methods alone cannot get good results
If only the lossy encoding method is used, the amount of data will be small, but for the computer desktop part, there will be obvious image loss. Usually, image degradation will occur at the boundary of text, lines, and image changes, and the image quality will deteriorate significantly. , which is unacceptable in occasions that require high image quality; and if only the lossless encoding method is used, the image quality of the desktop part can be fully guaranteed, but for the content in the video playback or photo browsing window, use a simple lossless The compression algorithm will not work, the image data is hardly compressed or only a small amount of compression, and the amount of data is large, which is also unacceptable for occasions that are sensitive to the amount of data such as storage capacity or network bandwidth.

Method used

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  • Coding optimization method and coding optimization device for images
  • Coding optimization method and coding optimization device for images

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Experimental program
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Embodiment 1

[0040] see figure 1 Shown is a schematic flow chart of Embodiment 1 of the image optimization encoding method of the present invention. In this embodiment, considering that different image types may be used in different time periods, the encoding that needs to be used for images in different time periods The method is set to meet the requirements of different image quality and data volume at the same time.

[0041] Such as figure 1 As shown, the image optimization encoding method in this embodiment includes steps:

[0042] Step S101: The encoding end receives the preset encoding mode to be used set by the user, where the preset encoding mode here is usually a lossless encoding mode for content such as desktop documents, and for content such as videos and photos , it is usually a lossy coding mode, and enter step S102;

[0043] Step S102: The encoding end uses the preset encoding mode set by the user to encode the image, and sends the preset encoding mode to the decoding end...

Embodiment 2

[0049] see figure 2 Shown is a schematic flow chart of Embodiment 2 of the image optimization encoding method of the present invention. In this embodiment, considering that when different types of images are used at the same time, the areas used by each type of image are relatively fixed. Therefore, by According to different image types, different regions are divided for different types of images, and each region uses its corresponding encoding mode.

[0050] Such as figure 2 As shown, the solution in this embodiment includes steps:

[0051] Step S201: The encoding end receives the lossless encoding range using the lossless encoding mode and the lossy encoding range using the lossy encoding mode set by the user. At this time, the above-mentioned preset encoding area includes the lossless encoding range and the lossy encoding range. The coding method includes a predetermined lossless coding mode and a predetermined lossy coding mode, and enters step S202;

[0052] Step S20...

Embodiment 3

[0061] see image 3 As shown, it is a schematic flow chart of the third embodiment of the image optimization coding method of the present invention. In this embodiment, considering the situation of mixed application, the image is divided into blocks first, and then each block is analyzed to determine whether each block Which encoding mode to use for the block. In this embodiment, lossless coding is performed on each block by using a lossless coding mode, and whether the block is suitable for a lossless coding mode or a lossy coding mode is judged according to a compression ratio of the lossless coding.

[0062] Such as image 3 As shown, the image optimization encoding method in this embodiment includes steps:

[0063] Step S301: The encoding end divides the image into blocks according to the predetermined block size. The predetermined block size here can be set according to needs, for example, 64*64 pixels. At this time, the above-mentioned preset encoding area includes eac...

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Abstract

The invention discloses a coding optimization method and a coding optimization device for images. The images are partitioned into blocks; each block is analyzed so as to select a proper coding mode for each block; for areas suitable for lossless coding, the areas are coded in a lossless coding mode; and for areas suitable for lossy coding, the areas are coded in a lossy coding mode; therefore, in spite of types of the images, the optimal image quality and the least data quantity can be achieved always.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to an image optimization encoding method and an image optimization encoding device. Background technique [0002] When computer raster images are stored and transmitted, in order to reduce the amount of data, various data compression algorithms are used to compress them, or it is called image coding. Coding methods for encoding images can be roughly divided into two types: lossless compression (lossless coding) and lossy compression (lossy coding). Lossless encoding does not damage the image, the process is reversible, and the decoded image is exactly the same as the undecoded image, but the compression ratio is usually not high, and the data volume is large, which is suitable for simple pictures and occasions with a large amount of repeated pixel data; while lossy encoding Compression is usually based on the situation, discarding some details in the visually accep...

Claims

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Application Information

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IPC IPC(8): H04N7/26H04N7/32H04N19/105H04N19/176
Inventor 谷新征刘先材蔡才冠冯海勇
Owner GUANGDONG VTRON TECH CO LTD
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