A Spaceborne Remote Sensing Image Compression Method Based on Adaptive Block Compression Sensing

A block-compressed sensing and remote sensing image technology, applied in the field of image processing, can solve the problems of high hardware requirements and high complexity, and achieve the effect of eliminating block effects and reducing reconstruction time

Active Publication Date: 2021-11-02
SHANGHAI RADIO EQUIP RES INST
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Problems solved by technology

The patent document "Compressed Sensing Image Reconstruction Method Based on Measurement Domain Block Saliency Detection" with publication number CN105678699A proposes to transform the measured values ​​of sub-blocks, and classify sub-blocks as salient blocks or non-salient blocks according to the transformed structure , assign different sampling rates at the same time, and perform secondary measurement on the image. This method is more complex and requires higher hardware requirements.

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  • A Spaceborne Remote Sensing Image Compression Method Based on Adaptive Block Compression Sensing
  • A Spaceborne Remote Sensing Image Compression Method Based on Adaptive Block Compression Sensing
  • A Spaceborne Remote Sensing Image Compression Method Based on Adaptive Block Compression Sensing

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Embodiment Construction

[0029] The present invention will be further elaborated below by describing a preferred specific embodiment in detail in conjunction with the accompanying drawings.

[0030] Such as figure 1 As shown, a spaceborne remote sensing image compression method based on adaptive block compressed sensing, including:

[0031] Step S1, divide an image into several sub-blocks, the size of the sub-blocks in this example is 64×64, but not limited to this value.

[0032] Step S2, obtain the gray level co-occurrence matrix of each sub-block, as shown in the following formula:

[0033]

[0034] in, Indicates the gray level co-occurrence matrix of the current sub-block, is the probability that a pixel with a gray level of α reaches a pixel with a gray level of β through a pre-set path relationship, α and β represent the gray level of the pixel, L represents the gray level of the image, and d k (k=1,2,3,4) is the path relationship between pixels on the image, respectively representing t...

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Abstract

The present invention provides a method for compressing space-borne remote sensing images based on self-adaptive block-compressed sensing. Aiming at the large amount of data of space-borne remote sensing images, if the entire image is compressed and sensed, the measurement matrix in the compression process needs to occupy more space. Storage space will also increase the complexity of refactoring. In the method of the present invention, after the image is divided into blocks, it is judged whether the sub-block continues to be divided into blocks according to the average entropy value of the gray level co-occurrence matrix of each sub-block; A different sampling rate is assigned to each sub-block. The invention reduces the space occupied by the observation matrix, eliminates block effects, and is suitable for compression of space-borne remote sensing images.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to block compressed sensing technology, in particular to a method for compressing remote sensing images through block compressed sensing, which can be used for compressing large-scale remote sensing images. Background technique [0002] Compared with other types of images, spaceborne remote sensing images have a larger amount of data and contain more texture information. The sampling frequency of traditional signals should be greater than twice the highest frequency of the signal, so following the Nyquist theorem to sample spaceborne images requires a higher sampling frequency. However, limited by the equipment conditions on the star, the traditional method cannot meet the high requirements for the storage capacity and processing speed of the compression encoding hardware. Compressed Sensing (CS) theory uses very little data to represent as much information as possible, and ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N19/86H04N19/176H04N19/132H04N19/42H04N19/426G06T7/45
CPCG06T2207/20004G06T7/45H04N19/132H04N19/176H04N19/42H04N19/426H04N19/86
Inventor 于欢王凤姣焦美敏吴雪微丁红晖顾泽凌李乃星
Owner SHANGHAI RADIO EQUIP RES INST
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