An Adaptive System for Gray Scale to RGB Image Conversion 1.Apurva B. Parandekar , M.E Scholar, Sipna College of Engineering & Technology, Amravati [email protected]2. Prof. Shital. S. Dhande Associate Professor, Sipna College of Engineering & Technology, Amravati [email protected]Abstract: We introduce a general technique for making colorless images into colored one. To achieve this we are introducing a technique for predicting color of a particular image. This technique helps in adding chromatic values to a colorless image and sophisticated measure for color transfer. Rather than choosing the entire color from the source to the target image, we transfer RGB colors from a palette to color gray scale components, by matching difference information between the images. Particular emphasis is placed on using color information to improve the assessment of colorless images to transfer only chromatic information and retain the original luminance values of the target image. This simple technique can be successfully applied to a variety of gray scale images and videos, provided that texture and luminance are sufficiently distinct. Keywords: Color map, Image Splitting, Pattern reorganization, RGB Color space, luminance, Reference Color Images, Object detection. 1. Introduction Gray scale image contains pixels which are not a RGB color pixels. Many applications convert a gray scale image into RGB color space but fail to preserve the original contents of a Gray Scale image. This project provides an emphasis on noise removal, color conversion and blur removing techniques. Colorization is a computerized process that adds color to a black and white print, movies and T.V program invented by Wilson MarkLey .It was initially used in 1970 to add color to footage of moon from the Apollo mission demand of adding color to gray scale image such as previous black and white movies, photos has been increasing. for e.g. in amusement field, many movies and video clips have been colorized by human labors and many gray scale images have been distributed as vivid images. In other fields such as archeology dealing with historical Gray scale data and security dealing with gray scale images by crime prevention camera, we can imagine easily that colorization techniques are useful. With respect to quality assessment, “the full -reference still-image problem is essentially solved”[7]. This recent, somewhat controversial statement by cocreator of the SSIM index, sounds surprising at first. Given that the SSIM index operates on grayscale data, color information is obviously not required to predict these distortions. Colors are extremely subjective and personal. They have a prominent feature by which we try to identify images better and improve the visual appearance of image. Colors can be added to grayscale images in order to increase the visual appeal of images such as to old black and white photos or movies or for the purpose of scientific illustrations to modify it to colorful and lively images. In addition, the information content of some scientific images can be perceptually enhanced with color by exploiting variations in chromaticity as well as luminance. Since different colors may have the same luminance value but vary in hue or saturation, the problem of colorizing grayscale images has no inherently “correct” solution. Due to these ambiguities, a direct prediction of color usually plays a large role in the colorization process. Where the mapping of luminance values to color values is automatic, the choice of the color map is commonly determined by a reference image. Here we address the color-related aspects of image splitting. We focus on full-reference measures, which will convert colorless image into color image [11]. Ideally, they reflect the actual visual mechanisms responsible for image color conversion. These mechanisms, however, are poorly understood, which applies especially to gray scale images. While standard methods accomplish this task by assigning pixel colors via a global color palette, our technique empowers the user to first select a suitable color image and then transfer the color of this image to the graylevel image at hand. 2. Analysis of Problem :- Changing gray scale image to color image is very complicated. Adding direct color to a gray scale image is not possible. One of the myths about the concept of changing a colorless image into an color image is that taking a color image and removing its color applying directly to the gray scale image. To change the color of colorless image we need to modify the existing methods. For applying color to a gray scale image, Apurva B Parandekar et al, Int.J.Computer Technology & Applications,Vol 5 (2),735-739 IJCTA | March-April 2014 Available [email protected]735 ISSN:2229-6093
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An Adaptive System for Gray Scale to RGB Image … Adaptive System for Gray Scale to RGB Image Conversion 1.Apurva B. Parandekar , M.E Scholar, Sipna College of Engineering & Technology,
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An Adaptive System for Gray Scale to RGB Image Conversion