Adaptive Histogram Equalization based Approach for SAR Image Enhancement: A Comparative analysis

With the explosion in the number of color digital images taken every day, the demand for more accurate and visually pleasing images is increasing. Images that have only one component in each pixel are called scalar images. Correspondingly, when each pixel consists of three separate components from three different signal channels, these are called color images. Image denoising, which aims to reconstruct a high-quality image from its degraded observation, is a classical yet still very active topic in the area of low-level computer vision. Impulse noise is one of the most severe noises which usually affect the images during signal acquisition stage or due to the bit error in the transmission. The use of color images is increasing in many color image processing applications. Restoration of images corrupted by noises is a very common problem in color image processing. Therefore, work is required to reduce noise without losing the color image features.

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Adaptive Histogram Equalization based Approach for SAR Image Enhancement: A Comparative analysis

Cited by 3 publications

References 12 publications

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An Improved Ensemble Extreme Learning Machine Classifier for Detecting Diabetic Retinopathy in Fundus Images

SSR-GAN: super resolution-based generative adversarial networks model for flood image enhancement

A Comparative Review for Color Image Denoising

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