Advanced Object Enhancement in an Image

Inclement dusty weather can have a substantial impact on image quality, as capturing photographs in such conditions frequently results in unwanted degradation such as weak contrast, insufficient colors, or color cast. Typically, images taken in dusty conditions have a color shift toward a brown hue, orange, or opaque yellow. As a result, such undesired artefacts must be efficiently handled in order for collected images to be more dependable for subsequent interpretations. As a result, image processing and computer vision applications such as surveillance, intelligent transportation systems, motion detection, object recognition, and object tracking, to mention a few, might be affected by such aberrations. Furthermore, these abnormalities can make it difficult to see relevant information in the collected photos. In this paper, the proposed method helps to enhance the quality of image by adjusting the image parameters and makes it useful for further interpretations. The PSNR range for an ideal image should be between 30 and 50. By altering the tuning parameter which is used to control color fidelity of image and calculating the intensification factors by obtaining the thresholding limit and membership function for tuning. The tuning outputs are concatenated to get the desired PSNR value of image.