Remote sensing image near-lossless compression hardware realization method based on improved JPEG-LS algorithm

Abstract

A remote sensing image near-lossless compression hardware realization method based on improved JPEG-LS algorithm comprises the steps (1) directly calculating to obtain a pixel reconstruction value by the pixel actual value of an input image and accomplishing the calculation in a single clock period by using a formula Rx=int[Ix/(2Near+1)]*(2Near+1), in the formula, the Rx and the Ix are respectively the pixel reconstruction value and actual value, the int is rounding operation, and the Near is a compression ratio control factor; (2) calculating a context environmental variable Q according to the obtained pixel reconstruction value, if Q is equal to 0, performing run coding, otherwise, going to a step (3) of performing conventional coding; (3) calculating the predictive value of the current pixel by the pixel reconstruction value according to the geometric position relation between the current pixel and the adjacent pixel; (4) calculating the residual value between the predictive value and actual value of the current pixel; and (5) performing Golomb coding after quantising the obtained residual value, and synchronously updating the parameter variable corresponding to the context environmental variable Q using the quantisation result.

Description

technical field [0001] The invention relates to an image compression method, in particular to an image data near lossless compression hardware implementation method based on the improved JPEG-LS algorithm. Background technique [0002] JPEG-LS (lnformation Technology-Lossless / near-lossless compression standard for continuous-tone still images) algorithm is an image compression standard formulated by the Joint Photographic Experts Group. Compared with other compression algorithms, JPEG- LS has higher compression performance in the field of lossless and near-lossless compression. JPEG-LS is developed on the basis of the LOCO-I algorithm. The LOCO-I algorithm achieves the purpose of compression by encoding the prediction residual value based on the context. The JPEG-LS standard algorithm uses two modes to encode pixels—run-length mode and normal mode. The normal mode performs Golomb coding on the prediction residual, while the run-length mode encodes the run-length, so that sm...

AI Technical Summary

Problems solved by technology

[0005] (1) Since the reconstruction value is needed to predict the following pixels instead of the actual value during encoding, and it takes several clock cycles to obtain the reconstruction value using the standard algorithm, it is difficult to compress the image timely and quickly by using this method;

[0006] (2) When calculating the context Q, multi-step serial calculations are required to calculate the Q value, the critical path is long, and it is difficult to meet the needs of real-time processing;

[0008] (4) When calculating the residual value, the floating-point multiplication is used in the quantization and inverse quantization of the standard algorithm, the calculation accuracy cannot be guaranteed, the calculation complexity is high, and it is difficult to meet the needs of fast processing;

[0009] (5) When parameter variables are updated, the standard algorithm involves more addition and subtraction operations and logical judgments, and many operations are serial operations, with high computational complexity, which affects the improvement of the operating speed of the entire system

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