Identifying and classifying image transforms
暂无分享,去创建一个
Image transforms are used extensively in image processing to convert one image form into another form. These transforms are either point-operation transforms or neighborhood-operation transforms. Point-operation transforms can be classified as either injective transforms or non-injective transforms depending on the type of mathematical function applied to the image and the image characteristics. In this paper we present a novel technique that can identify if an image was processed by a point-operation transform and classify the transform as being either injective or non-injective. The mapping function of the transform is also recovered in the process. The technique is applicable to both linear and non-linear transforms. Tests are conducted on real images to show the validity of our technique.
[1] Karsten Steffens. Injective Choice Functions , 1974, J. Comb. Theory, Ser. A.
[2] Milan Sonka,et al. Image Processing, Analysis and Machine Vision , 1993, Springer US.
[3] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[4] Anil K. Jain. Fundamentals of Digital Image Processing , 2018, Control of Color Imaging Systems.
[5] Dana H. Ballard,et al. Computer Vision , 1982 .