Abstract

Digital images are often obtained with contrast distortions due to different factors that cannot be avoided on many occasions. Various research works have been introduced on this topic, yet no conclusive findings have been made. Therefore, a low-intricacy multi-step algorithm is developed in this study for rapid contrast enhancement of color images. The developed algorithm consists of four steps, in that the first two steps include separate processing of the input image by the probability density function of the standard normal distribution and the softplus function. In the third step, the output of these two approaches is combined using a modified logarithmic image processing approach. In the fourth step, a gamma-controlled normalization function is applied to fully stretch the image intensities to the standard interval and correct its gamma. The results obtained by the developed algorithm have an improved contrast with preserved brightness and natural colors. The developed algorithm is evaluated with a dataset of various natural contrast degraded color images, compared against six different techniques, and assessed using three specialized image evaluation methods, in that the proposed algorithm performed the best among the comparators according to the used image evaluation methods, processing speed and perceived quality.

Highlights

  • Contrast enhancement (CE) is an important subject in digital image processing and computer vision [1]

  • A low-intricacy multi-step algorithm for adequate contrast enhancement of color images is developed. It consists of four distinct steps, in that each step contributes to the successful enhancement process

  • The first two steps include processing the input image with two different equations that can perform curvy transformations that can modify the contrast. The output of these equations is combined using a modified logarithmic image processing (LIP) model to get the features of both images

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Summary

Introduction

Contrast enhancement (CE) is an important subject in digital image processing and computer vision [1]. The global type is prevalent in enhancing digital images and providing good quality images. CE aims at improving the dynamic range of the image to provide better visual quality without creating any errors or losing details. The indirect category can be divided into several subgroups: methods that analyze the image to process its high and low frequencies, histogram processing techniques, and transformbased techniques. The key objectives of this study are to develop a low-intricacy multi-step algorithm for contrast enhancement and to provide rapid yet efficient processing for different contrast-distorted color images. The algorithm developed in this study consists of four distinct steps, for which each step contributes significantly to the enhancement process.

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