Texture Standards Of Measurement And Applications And Super-resolution Based On The Fractal Iterative Function System Since The Analogy Technology

Texture is an important concept in image processing and virtual reality. Its applicable research has been wide and in-depth, while its theory is still limited, especially texture doesn 7 have an unambiguous definition now, and there are no theory guidance to distinguish common images and texture. In this paper, we put off traditional opinion to consider texture as a certain type of image, while construct a new theory system instead. In our view, texture is an property of all image, difference in their density, which called texture standard property. An image has a larger texture standard property means it looks more like a texture intuitively. We researched a lot of images and textures to decide to use the color distribution histogram to measure this property, and obtained a good result.Meanwhile in the other field of image processing, super-resolution is an new highlight problem, whose object is clearing an low-resolution image to high-resolution version. There are some methods to do that now, however not only for application but also for theory, they all inevitably have large limitation. Recently a new idea base on machine study make a break to the limitation, but some shortcomings such as huge time burden of computation, dependent of training set remain. Via reading and studying many methods of super-resolution, we construct and research a model for common image edges, which lead to a mending to classic Image Analogies method called Self-image Analogies. By this idea, we explore sufficiently the information hidden in image itself and fractal character of image edges. Experiments proved this technology give a satisfied solution.