Frequency Domain Based MSRCR Method for Color Image Enhancement

-There are often serious discrepancy existing between the recorded image and the direct observation of the same scene. Human visual system is able to distinguish details and vivid colors in shadows and in scenes that contain illuminant shifts. In this paper it is presented an image enhancement algorithm called Multiscale Retinex with Color Restoration (MSRCR). The MSRCR algorithm tries to imitate human visual “computation” while observing scenes that contains lighting variations. MSRCR is an extension of a former algorithm called Single Scale center/surround Retinex (SSR) and its extension Multi Scale center/surround Retinex (MSR).MSRCR achieves simultaneous dynamic range compression, color consistency and lightness rendition. To reduce the computational effort the two dimensional filtering between surround function and the image function is performed in the frequency domain by finding the product of spectra of both the functions. Keywords—Retinex, Single Scale Retinex, Multi Scale Retinex, Multi Scale Retinex with Color Restoration, dynamic range compression, surrounding function. Introduction: Image enhancement improves the quality (clarity) of images for human viewing. Removing blurring and noise, increasing contrast, and revealing details are examples of image enhancement operations. Reducing the noise and blurring and increasing the contrast range could enhance the image. Image processing technology is used by planetary scientists to enhance images of Mars, Venus, or other planets. Doctors use this technology to manipulate CAT scans and MRI images. There are often serious discrepancy existing between the images and the direct observation of the real scenes. The human perception has natures of dynamic range compression and color rendition on the scenes. It can compute the details across a large range of spectral and lightness variations. So it is color constant. By comparison, the recorded films and other electric cameras, have no such computations before the scenes are recorded in the dynamic range limited media. Even with wide dynamic range imaging systems, the recorded images will not be seen same as real observation. This is because the dynamic range compression for perception of the recorded images is weaker than that for the scene itself. This could be explained as that in the real world, the wider angular extent helps to improve the dynamic range compression. The idea of Retinex was proposed as a model of lightness and color perception of the human vision. Obviously it is not only a model, but also could be developed to algorithms of image enhancement. Later single-scale Retinex (SSR) was defined as an implementation of center/surround Retinex. But depending on the special scale, it can either provide dynamic range compression (small scale) or tonal rendition (large scale). Superposition of weighted different scale SSR is obvious a choice to balance these two effects. This is multiscale Retinex (MSR). For color images, if the content is out of “gray world”, which means the spatial averages of three color bands are far from equal, the output will be forced to be gray by MSR. This problem could be solved by introducing weight factor for different channels in multiscale Retinex with color restoration (MSRCR). Image Enhancement using Retinex Algorithms: Land [1] first proposed the idea of Retinex as a model of lightness and color perception of the human vision. Obviously it is not only a model, but also could be developed to algorithms of image enhancement. Land gave more contributions on Retinex algorithm, evolving the concept from a random walk computation, to his latest version of a center/surround spatially opponent operation. The center/surround opponent operation is related to the neurophysiological functions of neurons in the primate retina, lateral geniculate nucleus, and cerebral cortex. Hurlbert [2] studied the lightness theories and found that they have a common mathematical foundation. Also the leaning problems for artificial neural networks suggested a solution with center/surround form. But that is not enough. The human vision does not determine the relative reflectances, but rather content dependent relative reflectances for arbitrary illumination conditions. Researchers defined a single-scale Retinex (SSR), which is an implementation of center/surround Retinex. But depending on the special scale, it can either provide dynamic range compression (small scale) or tonal rendition (large scale). Superposition of weighted different scale SSR is obvious choice to balance these two effects. This is multiscale Retinex (MSR). For color images, if the content is out of “gray world”, which means the spatial averages of three color bands are far from equal, the output will be forced to be gray by MSR. This problem could be solved by introducing weight factor for different channels in multiscale Retinex with color restoration (MSRCR). After MSRCR, generally the outputs will be out of IJREAT International Journal of Research in Engineering & Advanced Technology, Volume 2, Issue 4, Aug-Sept, 2014 ISSN: 2320 – 8791 (Impact Factor: 1.479) www.ijreat.org