Multiscale Total Variational Alggorithms for Denoising Natural Color Photos in Digital Photography
نویسندگان
چکیده
As digital photography rapidly replacing the traditional film photography as the photography of choice for all but a few devoted professionals, post image processing of natural color photos such as denoising becomes increasingly an integral part of digital photography. Although many denoising schemes have been designed, almost none specifically target natural color photos. Noise in natural color photos have special characteristics that are substantially different from those that have been added artificially. In this paper we propose the multiscale total variational method (MTV) for denoising. Standing alone the MTV method is effective in denoising monochromatic images. However, it demonstrates outstanding denoising capabilities for natural color images. Key to the success is the understanding of the characteristics of digital noise in natural color images as well as a non-traditional color space we have introduced specifically for the purpose. An automatic stopping criterion is applied to each channel to prevent over processing. 1. Noise In Natural Color Photos With the surging popularity of digital cameras, digital photography is rapidly replacing the traditional film photography as the photography of choice for virtually all but a few devoted professionals. In digital photography, post image processing is an integral part for obtaining better images even for the casual picture takers. Post image processing is especially important for people who are willing to go beyond point-and-shoot, and one of the key steps in image processing is denoising. All digital cameras today take color photos. (Some cameras allow for black-and-white images, but these are converted from color images using in-camera firmwares.) Noise is present in virtually all digital photos, and there are several sources for it. When light (photons) strike the image sensor, electrons are produced. These “photoelectrons” give rise to analog signals which are then converted into digital pixels by an Analog to Digital
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