Image Quality Enhancement using CLAHlet RetiGaussian Filter for Maize Leaf Images

Abstract

In this world of digitization, most of the data is in the form of images acquired using camera. Image enhancement plays a vital role in the quality improvement of digital images. In this work, a combined approach based on the contrast limited adaptive histogram equalization (CLAHE) and Retinex algorithm is proposed. It is a wavelet based Retinex algorithm with adaptive histogram equalization and gaussian filter. First, image is enhanced using CLAHE, image is decomposed using Daubechies wavelet and then followed by the Retinex algorithm, which used low frequency components to enhance the image. Lastly, a gaussian filter is used to smoothen the image. The dataset of maize leaf disease is used for the analysis of quality enhancement and denoising. It is clear from the results that the proposed method improves the quality by reducing the noise of the maize leaf images. Theses refined images can be used for maize leaves disease detection and classification system to achieve high accuracy.

Adams Algorithm with Generative Adversial Network for Maize Leaf Disease Classification

“…In 2023, Handaet al [25] have tried image processing method to detect the maize leaf images. Initially, the input images of the maize leaves were enhanced through CLAHE.…”