An Analytical Review on Image Enhancement Techniques

This study presents an organized analysis and presentation of many existing image enhancing approaches. The fundamental idea behind image enhancement is to change images informational content so that it is more suited for certain purposes. Image Enhancement is the most significant part of Digital Image Processing (DIP). It is required to mitigate noise, blur, color distortion and artifacts. There are a lot of development in every aspect of society indeed, but still, there is lack of reliable, complete clear and availability and flow of visual, text and audio information, which is sometimes life-threatening in many sensitive areas, Image enhancement technology very much depends upon the type of picture and the domain for which the image is going to be used. There is a requirement of reliable visual data in most sensitive areas such as medical, geographical, and social security, seismology and weather forecasting. Image improvement of low-light images has grown in importance as computer vision research has become more complex due to the increased demands of the field. In this paper, first the fundamental techniques of image enhancement has been reviewed for understanding purpose and then findings together with the many benefits and drawbacks of the mentioned approaches as well as the potential for further study in this field has been presented. More Emphasize on model-based techniques has been given in this article, since they are interpretable and don’t require labeled training data.