A Lossless Compression Method for Inhomogeneity Residuals of Line Scan Infrared Imaging

Abstract

The invention discloses a lossless compression method for a linear scanning infrared imaging heterogeneity residual. The method comprises the following steps of extracting a direct-current component of each column of an image by using Fourier decomposition and rounding in order to obtain an image column direct-current component array DC; subtracting a value of the corresponding column in the direct-current component array DC from each pixel in each column in order to obtain an image, wherein the heterogeneity of the pixels in the image in a column direction is removed; carrying out predictioncompression coding of adaptive discrimination of a dynamic range of blocks on the image without the heterogeneity in the column direction; carrying out lossless one-dimensional prediction compressioncoding on a column direct-current component vector DC; and respectively transmitting the two types of compressed code streams. According to the method, a Fourier decomposition method is used for extracting the heterogeneity of the pixels in the image in the column direction, the heterogeneity residual of the image is reduced, the heterogeneous components and the image without the heterogeneity aresubjected to lossless compression, and the compressed code streams are transmitted respectively, so that a compression ratio is effectively improved, and a problem of limited bandwidth is relieved.

Description

technical field [0001] The invention belongs to the field of aerospace spaceborne image compression, and more specifically relates to a lossless compression method for non-uniform residuals of line-scanning infrared imaging. Background technique [0002] Spaceborne images have a wide format and a large amount of data. Compression technology must be used to reduce the amount of data transmission and alleviate the contradiction between limited transmission bandwidth and large amount of transmitted data. If there are high-risk and high-value targets in satellite images, lossless compression technology must be used in order not to lose target information. Compared with lossy compression, the compression ratio achieved by lossless compression is very limited, and its compression performance mainly depends on the correlation of the image itself and the effective dynamic range of the data. The stronger the image correlation is, the smaller the effective dynamic range of the image ...

AI Technical Summary

Problems solved by technology

[0003] Non-uniformity residuals often appear in satellite images based on linear pixel scanning imaging. The main reason for this is that there are differences in the non-uniformity responses of each pixel on the linear column during the scanning imaging process of the linear optical and electrical sensor devices. It causes the phenomenon that the gray value of the image data in a certain direction is continuously high or low, resulting in the phenomenon of "banding" in the image

The non-uniform residuals of each pixel in the line cover up the information that the scene in the real world often changes continuously, which reduces the original correlation between pixels, and the existing lossless compression technology cannot make full use of the correlation for predictive coding and improve the compression ratio. , which adversely affects data transmission with limited bandwidth

[0004] On the one hand, the various existing lossless compression methods do not consider the influence of the degradation characteristics of the image itself on the correlation between pixels in the image, and on the other hand, they do not consider the characteristics of the image data itself, and adopt a fixed bit width mode, which cannot be adjusted adaptively. The bit width used in predictive coding makes it impossible to effectively compress image data losslessly, so the compression ratio is low and the problem of bandwidth limitation cannot be alleviated

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