CAJ | 학술논문

针对数字图像可逆水印的高嵌入容量和不可见性的权衡问题,该文提出一种基于分块自适应压缩感知的可逆水印算法(Reversible Watermarking Algorithm Based on Block Adaptive Compressed Sensing, BACS-RWA).该算法对载体图像分块,利用周围块与目标块的统计关系判断块类型,自适应地选择容量参数进行分块压缩感知,并利用整数变换嵌入水印;为提高水印嵌入容量将水印嵌入到经压缩感知后的平滑和普通载体图像块中,复杂载体图像块不做处理,以确保图像质量和不可感知性;采用分块压缩重构算法和可逆整数变换来恢复载体图像.通过对不同纹理图像实验并与同类算法对比,结果表明:当以Plane为载体图像时,最佳嵌入容量达1.87 bpp.分块自适应压缩感知理论的引入使算法具有良好的综合性能,在提高嵌入容量的同时,又能有效地降低嵌入数据后对原始图像质量的影响.
침대수자도상가역수인적고감입용량화불가견성적권형문제,해문제출일충기우분괴자괄응압축감지적가역수인산법(Reversible Watermarking Algorithm Based on Block Adaptive Compressed Sensing, BACS-RWA).해산법대재체도상분괴,이용주위괴여목표괴적통계관계판단괴류형,자괄응지선택용량삼수진행분괴압축감지,병이용정수변환감입수인;위제고수인감입용량장수인감입도경압축감지후적평활화보통재체도상괴중,복잡재체도상괴불주처리,이학보도상질량화불가감지성;채용분괴압축중구산법화가역정수변환래회복재체도상.통과대불동문리도상실험병여동류산법대비,결과표명:당이Plane위재체도상시,최가감입용량체1.87 bpp.분괴자괄응압축감지이론적인입사산법구유량호적종합성능,재제고감입용량적동시,우능유효지강저감입수거후대원시도상질량적영향.
@@@@To balance high embedding capacity and imperceptibility of reversible watermarking algorithm for digital images, a novel Reversible Watermarking Algorithm based on Block Adaptive Compressed Sensing (BACS-RWA) is proposed. The host image is divided into blocks and the types of these blocks are determined with the statistical relationship between the surrounding image blocks and the target block. The capacity parameters are adaptively selected to do block compressed sensing and the watermarking is embedded with integer transformation. In order to improve embedding capacity, the smooth and normal blocks of compressed sensing host image are used to embed watermarking. Complex blocks are not processed to insure image quality and imperceptibility. Reconstruction algorithm of block compressed sensing and reversible integer transformation are used to reconstruct the host image accurately. Simulation of this algorithm is performed on different texture images and compared with similar algorithms. Experimental results show that the optimal embedding capacity can reach up to 1.87 bpp when Plane is used as host image. The introduction of block adaptive compressed sensing theory leads to better comprehensive performance. It can not only improve embedding capacity, but also reduce effectively the influence of embedding data on the quality of the host image.