Histogram equalization

About: Histogram equalization is a research topic. Over the lifetime, 5755 publications have been published within this topic receiving 89313 citations.

Use of histogram equalization in image processing for image enhancement

Abstract: — Digital Image Processing is a rapidly evolving field with the growing applications in science & engineering. Image Processing holds the possibility of developing an ultimate machine that could perform visual functions of all living beings. The image processing is a visual task, the foremost step is to obtain an image i.e. image acquisition then enhancement and finally to process. In this paper there are details for image enhancement for the purpose of image processing. Image enhancement is basically improving the digital image quality. Image histogram is helpful in image enhancement. The histogram in the context of image processing is the operation by which the occurrences of each intensity value in the image is shown and Histogram equalization is the technique by which the dynamic range of the histogram of an image is increased.

Brightness preserving image enhancement based on a gradient and intensity histogram

Abstract: We present a straightforward brightness preserving image enhancement technique. The proposed method is based on an original gradient and intensity histogram (GIH) which contains both gradient and intensity information of the image. This character enables GIH to avoid high peaks in the traditional intensity histogram and, thus alleviate overenhancement in our enhancement method, i.e., gradient and intensity histogram equalization (GIHE). GIHE can also enhance the gradient strength of an image, which is good for improving the subjective quality since the human vision system is more sensitive to the gradient than the absolute intensity of image. Considering that brightness preservation and dynamic range compression are highly demanded in consumer electronics, we manipulate the intensity of the enhanced image appropriately by amplifying the small intensities and attenuating the large intensities, respectively, using a brightness preserving function (BPF). The BPF is straightforward and universal and can be used in other image enhancement techniques. We demonstrate that the proposed method can effectively improve the subjective quality as well as preserve the brightness of the input image.

A New Enhancement Approach for Enhancing Image of Digital Cameras by Changing the Contrast

Abstract: This article introduces a new image Enhancement approach suitable for digital cameras. High contrast images are common in the scenes with dark shadows and bright light sources. It is difficult to show the details in both dark and light areas simultaneous on most display devices. For solving this problem, there are many methods of image enhancement proposed to improve the quality of the images. However, most of them often get poor results if the images are high contrast and have wide dynamic range. This method for enhancing the highcontrast digital camera images, which enhances the global brightness and contrast of images while preserving details. It is based on a two-scale decomposition of the image into a base layer, encoding large-scale variations, and a detail layer. The base layer is obtained using an edge preserving filter that is a weighted average of the local neighborhood samples, where the weights are computed based on temporal and radiometric distances between the center sample and the neighboring samples. Only the base layer image is enhanced automatically by using histogram equalization method, thereby preserving detail. The experimental results show the proposed method provides a significant enhancement for the high-contrast images and requires no parameter setting. And also in this work processing cost reduction when the new approach is followed.

Smoothing and enhancement algorithms for underwater images based on partial differential equations

Abstract: The formulation and application of an algorithm based on partial differential equations for processing underwater images are presented. The proposed algorithm performs simultaneous smoothing and enhancement operations on the image and yields better contrast enhancement, color correction, and rendition compared to conventional algorithms. Further modification of the proposed algorithm and its combination with the powerful contrast-limited adaptive histogram equalization (CLAHE) method using an adaptive computation of the clip limit enhances the local enhancement results while mitigating the color distortion and intrinsic noise enhancement observed in the CLAHE algorithm. Ultimately, an optimized version of the algorithm based on image information metric is developed for best possible results for all images. The method is compared with existing algorithms from the literature using subjective and objective measures, and results indicate considerable improvement over several well-known algorithms.

Artificial landmark tracking based on the color histogram

Abstract: For the fast and accurate self-localization of mobile robots, landmarks can be used very efficiently in the complex workspace. In this paper, we propose a simple color landmark model for self-localization and a fast landmark detection and tracking algorithm based on the proposed landmark model. We develop a color landmark with symmetric and repetitive structures, which shows invariant color histogram characteristics under some geometric distortions. Detection and tracking of the model are accomplished by a factored sampling technique in which color similarity is estimated by the color histogram intersection. We also use the color similarity to update the color histogram model of the landmark model for robust tracking under illumination change. We demonstrate the feasibility of the proposed technique through experiments in cluttered indoor environments.