US 11,936,869 B2
Image compression sampling method and assembly
Yuan Ge, Jiangsu (CN); Hongzhi Shi, Jiangsu (CN); and Jian Zhao, Jiangsu (CN)
Assigned to INSPUR SUZHOU INTELLIGENT TECHNOLOGY CO., LTD., Jiangsu (CN)
Appl. No. 18/246,470
Filed by INSPUR SUZHOU INTELLIGENT TECHNOLOGY CO., LTD., Jiangsu (CN)
PCT Filed Jul. 30, 2021, PCT No. PCT/CN2021/109503
§ 371(c)(1), (2) Date Mar. 23, 2023,
PCT Pub. No. WO2022/110867, PCT Pub. Date Jun. 2, 2022.
Claims priority of application No. 202011363452.8 (CN), filed on Nov. 27, 2020.
Prior Publication US 2023/0353739 A1, Nov. 2, 2023
Int. Cl. G06K 9/36 (2006.01); H04N 19/119 (2014.01); H04N 19/126 (2014.01); H04N 19/132 (2014.01); H04N 19/176 (2014.01); H04N 19/88 (2014.01); H04N 19/895 (2014.01)
CPC H04N 19/126 (2014.11) [H04N 19/119 (2014.11); H04N 19/132 (2014.11); H04N 19/176 (2014.11); H04N 19/88 (2014.11); H04N 19/895 (2014.11)] 20 Claims
OG exemplary drawing
 
1. An image compression sampling method, comprising:
performing sparse representation on a target image by using an initial sparse matrix to obtain an initial sparse representation result;
quantifying the initial sparse representation result to obtain an optimized sparse representation result, and optimizing the initial sparse matrix according to the optimized sparse representation result to obtain an optimized sparse matrix;
constructing a product matrix by using the optimized sparse matrix and an initial measurement matrix, and adjusting absolute values of off-diagonal elements in the product matrix to be less than a correlation threshold;
performing singular value decomposition on the adjusted product matrix to obtain a diagonal matrix and a left singular matrix, and updating the diagonal matrix according to a quantity of samplings of the initial measurement matrix; and
optimizing the initial measurement matrix by using the left singular matrix and the updated diagonal matrix to obtain an optimized measurement matrix, and collecting image data by using the optimized sparse matrix and the optimized measurement matrix.