To Improve the Insect Pests Images- A Comparative Analysis of Image Denoising Methods

: Pest, Plant disease, climate change, and disaster are the major factor to determine the yeild of the plant. Pest inthe plants are identified in different methods. To process the images with machine vision models’ the quality of images isan important concern. Noise and unwanted artifacts integrated with the images at the time of acquisition and transmission. Noise is introduced in the images due to transmission, environment distortion, and sensor qualities. In this regard, some solutions related to the post-image-acquisition are required to enhance such issues. In this, image denoiser plays an important role to enhance the quality and minimize the noises in images. However, to preserve details of images a comparative analysis of related image denoising algorithms is conducted. In this study, the authors cover three types of filters to minimize the noise of insect pests’ images to find better ones. The experiment of the comparative study revealed that the Total Variation (TV) algorithm gives better results as compared to another denoising algorithm at different noise levels.