Gray Image Scrambling Algorithm And Evaluation Method

With the rapid development of multimedia technology, information technologyand the Internet, the amount of data is large and difficult to store and transmit imagesand more frequently appear on the computer screen, the image information isvulnerable to the illegal attack interception in the network storage and transmissionprocess, leading to more serious consequences and losses, therefore, the safety andeffectiveness of the information has increasingly become the focus of attention,reliable encryption for digital image processing and thus is particularly necessary.The digital image scrambling technology is an effective of information hidingpre-processing method and image encryption means. The digital image scrambling isa more important image encryption algorithms, its main purpose is to disrupt thegiven image, which makes it unable to find the true meaning of the expression of theoriginal image by the human visual system and the computer system. Afterlong-term exploration, the researchers proposed a lot of the set of scramblingalgorithm, these algorithms are mainly two types-pixel position and pixel valuesscrambling. Which pixel location scrambling to study the majority, but thisalgorithm has many deficiencies, such as: transform cyclical recovery security issues,scrambling image size requirements, scrambling degree is less than ideal, scramblingis not stability, scrambling repeated iteratively, scrambling extremely inefficient; Inaddition, the pixel values Scrambling study is relatively less, but this algorithm isbetter than the former. Therefore, based on the disadvantages of existing algorithmsproposed two types of image scrambling algorithm, and get an effective scramblingdegree evaluation algorithm by scrambling algorithm performance in-depth anddetailed analysis.A Soma cube box match the image scrambling algorithm, is for image pixelposition scrambling algorithm shortcomings and proposed the idea of matchingbased on the Soma cube box. Soma cube is the same size by27blocks in accordancewith7different rules Soma components splicing, for splicing, there are many ways, and it is a three-dimensional model, so it for image scrambling need to operate in athree-dimensional model, which can greatly enhance the degree of scrambling.Firstly, Soma block in accordance with the composition of the original image block,and select the Soma cube arbitrary two splicing, one of the original picture elementssplicing, another set of scrambled image mosaic, two splicing correspondingconversion, so you can image scrambling. The experimental results and thequalitative and quantitative analysis of the existing pixel position scramblingalgorithm, which has improved greatly in terms of visual effects, scrambling degree,anti-attack effect.A local heap and the Gray code image scrambling algorithm, which is based onthe pixel values scrambling. Firstly, the original image local heap adjusted, then theGray code conversion is applied on the image after the adjustment, change the valuesof image pixel, achieve gray image scrambling. Experiment confirmed and thequalitative and quantitative analysis, the algorithm to achieve the desired results inthe scrambling effect, scrambling degree, anti-attack capability, and the degree ofwhite noise, and truly realize the image scrambling.Wavelet domain local standard deviation of image scrambling evaluationmethod is proposed based on the calculation of large and complex of the existingimage scrambling algorithm. Local standard deviation algorithm applied to thewavelet domain, frequency domain analysis of image scrambling degree, thismethod is simple and effective, compared to many of the existing spatial domainscrambling degree evaluation algorithm, the algorithm higher accuracy. Andexperiments show that our algorithm with different scrambling algorithm fordifferent image scrambling effect evaluation can accurately reflect the relationship ofthe number of scrambling and scrambling degree, and is consistent with humanvisual perception, which proves the algorithm validity and rationality.