Method, device, equipment and system for selecting optimal quantization parameter during image compression

Abstract

The embodiment of the invention discloses a method, device, equipment and system for selecting an optimal quantization parameter during image compression. The method comprises the following steps: establishing a regression model function between an image content feature and an optimal quantization parameter, calculating image content characteristics of a to-be-compressed image, obtaining predictedquantization parameters of the to-be-compressed image according to the regression model function, taking a range obtained by floating preset data up and down by taking the predicted quantization parameter as a center as a quantization parameter range, and selecting the quantization parameter with a highest compression quality evaluation index in the quantization parameter range as an optimal quantization parameter. By utilizing each embodiment of the invention, the optimal quantization parameter can be quickly selected on the premise of meeting the code length threshold and ensuring the imagecompression quality.

Description

technical field [0001] The present invention relates to the technical field of digital image processing, in particular to a method, device, device and system for selecting optimal quantization parameters during image compression. Background technique [0002] With the continuous development of multimedia technology, informatization is closely related to people's life. In today's information explosion, the contradiction between the huge amount of data and information storage space is becoming increasingly prominent, especially in digital image communication. The 24-bit true color image of 1024×1024 has a data volume of 3MB. In the actual image storage process, because the storage space is always limited, the code length threshold is often given so that the code length after compression is less than the code length gate. limit. When the coding length is limited, the optimal quantization parameter is obtained by selecting the quantization parameter, so that the code length of ...

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Problems solved by technology

[0004] Existing image compression standards include JPEG, JPEG-LS, and BPG, etc. Among them, for the JPEG standard, the quantization parameters are usually solved by an iterative method, which requires a large amount of calculation and takes a long time, which is not conducive to practical application; for JPEG-LS Compression standards, generally solve the quantization parameters through the method of feedback adjustment. Among them, the first-order code rate control method proposed by Xu Yanling in the article "JPEG-LS Image Compression Dynamic Code Rate Control Strategy" adopts the method of array adjustment and fixed threshold value to obtain quantization parameters, but this method has poor control effect

BPG is an image format proposed in 2014. Its image compression algorithm is based on the advanced video compression protocol HEVC (High Efficiency Video Coding). The optimal quantization parameters are obtained under the following conditions, and there is no research on the rate control algorithm of the BPG compression format

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