A method to quantify difference for video code processing and its device

Abstract

The provided nonlinear differential quantizer for video coding system comprises: a first differential quantization unit with a quantizing subcell to convert every difference between near pixel values of video information into relative discrete step length to be scaled for full size of pixel amplitude, an overflow checkup subcell to check and correct the upper and / or overflow according to pixel amplitude. This invention can generate nonlinear feature coincident with human visual reaction system, and holds all HF components for well clearness and resolution.

Description

technical field [0001] The present invention generally relates to the field of video coding and compression, and more specifically relates to a difference quantization method and device used in video coding processing. Background technique [0002] Existing video coding implementations are based on frequency-domain algorithms, such as those encoder algorithms that apply cosine transforms in the frequency domain. But these encoder algorithms have some drawbacks. For example, semiconductor implementations of real-time frequency-domain encoders typically require more than 8 million transistors. Frequency domain coders use quantized frequency components to reduce the amount of encoded information. This may result in the loss of some high frequency components, reducing the clarity and resolution of the video. VICOMP (Video Coding and Compression System and Device) is a digital video coding scheme based on high-quality, real-time, high-efficiency video coding (high compression ...

AI Technical Summary

Problems solved by technology

However, because real video signals contain low-frequency components that account for the majority, 2 times the sampling frequency will cause oversampling of low-frequency components

Therefore, there will be a considerable amount of redundancy in the sampled signal

[0008] 2. Oversampling to bit resolution - Redundancy also arises from oversampling the resolution (number of bits) per sample

[0010] 4. Noise filtering - because of the limited dynamic range of the video image sensor, the video contains a large amount of white noise. This white noise is completely random, which means it reduces redundancy and reduces compression rate

[0012] 6. Occurrence redundancy - some video elements can be expected to have a higher frequency than others

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