The aim of this paper is to present a transform-based framework for color image enhancement which processes all three color components (R,G,B) simultaneously. In this framework, the image enhancement procedure is supported by a two-dimensional discrete quaternion Fourier transform and the new multi-frequency band α-rooting concept. Moreover, we introduce a simple measure to evaluate the quality...

In this paper, a novel color texture image classification based on HSV color space, wavelet transform, and motif patterns is introduced. Traditionally, RGB color space is widely used in digital images and hardware. However, RGB color space is not accurate in human visual perception and statistical analysis. Therefore, HSV color space is applied to obtain more accurate color statistics for extra...

This paper proposes a new method for enhancing the contrast of color images based on Wavelet Transform and human visual system. The RGB (red, green, and blue) values of each pixel in a color image are converted to HSV (hue, saturation and value) values. To the V (luminance value) components of the color image, Wavelet Transform is applied so that the V components are decomposed into the approxi...

The large numbers of images has posed increasing challenges to computer systems to store and manage data effectively and efficiently. This paper implements a CBIR system using different feature of images through four different methods, two were based on analysis of color feature and other two were based on analysis of combined color and texture feature using wavelet coefficients of an image. To...

This paper presents a parallel implementation of color image segmentation algorithm using multiresolution technique. The idea is to achieve the complete and significant objects in the image using contourlet transform based image segmentation and to explore current multi-core architectures present in commercial processors in order to speed up the segmentation process for large size images. The a...

A framework for color image segmentation is presented, which combines color histogram analysis and region merging approach. Its main goal is to segment an image at material boundaries (i.e., discontinuities of reflectance properties) while ignoring spatial color inhomogeneities of uniformly pigmented (colored) objects, caused by accidents of illumination and viewing geometry. Theoretical examin...

In this paper, we propose a numerical strategy to define a multiscale analysis for color and multicomponent images based on the representation of data on a graph. Our approach consists in computing the graph of an image using the psychovisual information and analysing it by using the spectral graph wavelet transform. We suggest introducing color dimension into the computation of the weights of ...

In this paper a new visual feature, binary wavelet transform based histogram (BWTH) is proposed for content based image retrieval. BWTH is facilitated with the color as well as texture properties. BWTH exhibits the advantages of binary wavelet transform and histogram. The performance of CBIR system with proposed feature is observed on Corel 1000 (DB1) and Corel 2450 (DB2) natural image database...

In this paper a fast and effective noise-resistant method for image retrieval has been proposed. In this method, first, the image is decomposed into different frequency layers using complex wavelet transform so as to make it possible to extract the texture features of the image. Thereafter, in the HSV color space, each layer is quantized into 166 different colors and the color histogram is calc...