Self-adaptive sampling rate based image sampling method

Abstract

The invention discloses a self-adaptive sampling rate based image sampling method. The method includes the steps: calculating a variance sigma 2 of an input image, sampling the whole image by a first sampling rate f1 when the variance sigma 2 is smaller than a preset first threshold value T1, or sampling the whole image by a sampling rate f3 when the variance sigma 2 is larger than or equal to a preset fourth threshold value T4, or when the variance sigma 2 is larger than or equal to T1 and smaller than T4, making an image layer l equal to 1, partitioning the image into a plurality of image blocks, obtaining a local variance sigma' 2 of each image block, judging whether the local variance sigma' 2 meeting a preset layering stop condition S or not, if yes, calculating a mean M sigma of local variance sigma' 2 of all image blocks, and selecting different sampling rates adaptively according to the mean M sigma in different ranges. Since the sampling rates are dynamically selected according to local features of images, sampling numbers required for image reconstruction can be decreased to different degrees to enable small space occupancy after subsequent image compression and coding. In addition, the self-adaptive sampling rate based image sampling method has the advantages of simplicity and easiness in implementation, wide application range and the like.

Description

technical field [0001] The invention relates to image compression coding technology, in particular to an image sampling method based on adaptive sampling rate. Background technique [0002] The traditional technology uses a measurement matrix under a single sampling rate (or sampling frequency) for sampling in the image compression codec method. The measurement matrix under a single sampling rate can obtain a better reconstruction effect when the sampling rate is higher. [0003] However, the existing technology has the following technical defects: due to the different local characteristics of different types of image blocks, although the number of samples at a low sampling rate is reduced, it is difficult to ensure that each block has a high reconstruction quality, and the high sampling rate will It causes waste of resources, thus requires a large number of samples and a large amount of storage space, making hardware implementation difficult. Contents of the invention ...

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Problems solved by technology

[0003] However, the existing technology has the following technical defects: due to the different local characteristics of different types of image blocks, although the number of samples at a low sampling rate is reduced, it is difficult to ensure that each block has a high reconstruction quality, and the high sampling rate will It causes a waste of resources, which requires a large number of samples and a large amount of storage space, making hardware implementation difficult

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