Demosaicing of Color Images by Accurate Estimation of Luminance

Digital cameras acquire color images using a single sensor with Color filter Arrays. A single color component per pixel is acquired using color filter arrays and the remaining two components are obtained using demosaicing techniques. The conventional demosaicing techniques existent induce artifacts in resultant images effecting reconstruction quality. To overcome this drawback a frequency based demosaicing technique is proposed. The luminance and chrominance components extracted from the frequency domain of the image are interpolated to produce intermediate demosaiced images. A novel Neural Network Based Image Reconstruction Algorithm is applied to the intermediate demosaiced image to obtain resultant demosaiced images. The results presented in the paper prove the proposed demosaicing technique exhibits the best performance and is applicable to a wide variety of images

Lossless compression of color filter array mosaic images with visualization via JPEG 2000

Digital cameras have become ubiquitous for amateur and professional applications. The raw images captured by digital sensors typically take the form of color filter array (CFA) mosaic images, which must be "developed" (via digital signal processing) before they can be viewed. Photographers and scientists often repeat the "development process" using different parameters to obtain images suitable for different purposes. Since the development process is generally not invertible, it is commonly desirable to store the raw (or undeveloped) mosaic images indefinitely. Uncompressed mosaic image file sizes can be more than 30 times larger than those of developed images stored in JPEG format. Thus, data compression is of interest. Several compression methods for mosaic images have been proposed in the literature. However, they all require a custom decompressor followed by development-specific software to generate a displayable image. In this paper, a novel compression pipeline that removes these requirements is proposed. Specifically, mosaic images can be losslessly recovered from the resulting compressed files, and, more significantly, images can be directly viewed (decompressed and developed) using only a JPEG 2000 compliant image viewer. Experiments reveal that the proposed pipeline attains excellent visual quality, while providing compression performance competitive to that of state-of-the-art compression algorithms for mosaic images