Conditional entropy coding method, device and equipment
By using continuous index values and cumulative distribution functions in the conditional entropy model to find tables, the problem of high coding complexity of conditional entropy models in the prior art is solved, and more efficient image encoding and more reliable coding results are achieved.
CN120166231APending Publication Date: 2025-06-17INST OF ADVANCED TECH UNIV OF SCI & TECH OF CHINA +2
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Patent Information
- Application Number
- CN202510428878.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-03
- Publication Date
- 2025-06-17
AI Technical Summary
Technical Problem
The existing conditional entropy model uses complex probability prediction models in image encoding, resulting in high encoding complexity and low encoding efficiency.
Method used
The continuous index value of the element to be encoded is determined through the conditional entropy model, and the discrete index value is determined through simple mapping operations. The corresponding cumulative distribution function is obtained from the pre-stored cumulative distribution function lookup table, and entropy encoding is performed.
Benefits of technology
It reduces the computational complexity of encoding, improves coding efficiency, and reduces floating-point calculation errors, and improves the reliability of encoding.
✦ Generated by Eureka AI based on patent content.
Abstract
The embodiment of the invention provides a conditional entropy coding method, device and equipment, and relates to the technical field of image processing. The method comprises the following steps: determining a continuous index value corresponding to a to-be-coded element through a conditional entropy model; determining a discrete index value corresponding to the continuous index value, and determining probability distribution corresponding to the discrete index value from a preset probability distribution set; determining a cumulative distribution function corresponding to the probability distribution from a pre-stored cumulative distribution function lookup table; and entropy coding is performed on the to-be-coded element through the cumulative distribution function. Therefore, only one continuous index value needs to be predicted, the discrete index value is determined through simple mapping operation, then the cumulative distribution function corresponding to the discrete index value is directly obtained through the pre-stored cumulative distribution function lookup table, and the complex process of dynamically calculating the cumulative distribution function is avoided. According to the method, the coding calculation complexity is reduced, and the coding efficiency is improved.
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