Method for coding hybrid image

Abstract

The invention discloses a method for coding a hybrid image efficiently. The method comprises the following steps of: applying base color and an index table coding method to interframe coding of the hybrid image; sequencing a base color value obtained by clustering matching blocks and a base color value obtained by clustering the current coding blocks during transmission of the base color; correspondingly making a difference to obtain a residual value of the base color; transmitting a difference value by using exponential Golomb coding; adaptively selecting a transmission mode of the base color by taking the minimum code rate as a principle and adopting an equal length coding method of the base color during the transmission of the base color; marking the transmission code with a bite; and obtaining a base color index of each pixel in a prediction block according to the value of each pixel in the prediction block, the base color value of the current coding block and the principle of minimum Euclidean distance during the transmission of an index map, taking the base color index of each pixel as a reference index of the current coding block, and using a bite for showing whether the index of each pixel is matched with the reference index of a corresponding position.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for encoding mixed images. Background technique [0002] In existing technologies, coding of mixed images can be roughly classified into the following three categories. [0003] 1. Method based on image coding: [0004] This method still uses the traditional encoding framework to encode the mixed image, but uses different quantization steps for different regions. For blocks containing text and graphics, the reconstruction effect after encoding will be very blurred, so when quantizing these blocks Reduce the quantization step size, allocate more bits to it, and make its reconstruction quality as good as possible. But for a fixed number of bits, if more bits are allocated for text and graphic blocks, then the number of bits allocated for natural image blocks will be correspondingly reduced, so generally speaking, this method still cannot achieve good...

AI Technical Summary

Problems solved by technology

But this method has some disadvantages: firstly the gain largely depends on the segmentation algorithm, that is how to divide the image into foreground and background

Second, the split holes will damage the encoding effect if they are not processed.

Third, separately encoding the text color of the background layer and the text shape of the b

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