• Dr. G. Sunil Kumar
• P Annapurna
• P Bhavana Sai
• N Sai Venkat
• P Hemanth

In sand-dust weather conditions, images often suffer from low contrast, color distortion, and blurriness, severely impacting their clarity. To address this, we introduce a method that adjusts pixel colors adaptively using the mean and standard deviation of chromatic histograms. This method ensures that each color component is corrected based on the statistical properties of the green component, preserving the mean green value. Additionally, we employ a green-mean-preserving color normalization technique. Furthermore, we utilize the YCbCr color space method to enhance contrast and accuracy. By separating the image into its Hue, Saturation, and Intensity components and enhancing them individually, we can retain detailed information. Finally, we enhance the luminance component using CLAHE (Contrast Limited Adaptive Histogram Equalization), resulting in the output termed L-CLAHE. Through quantitative evaluations, our method demonstrates significant improvement in images captured during sand-dust weather compared to other techniques.

Sand-dust image enhancement, color normalization, green-mean preserving, maximum overlapped histogram, coincident chromatic histogram

"ENHANCEMENT OF SAND DUST IMAGES USING HISTOGRAM AND L-CLAHE TECHNIQUE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.g502-g507, June-2024, Available :http://www.jetir.org/papers/JETIR2406658.pdf

"ENHANCEMENT OF SAND DUST IMAGES USING HISTOGRAM AND L-CLAHE TECHNIQUE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. ppg502-g507, June-2024, Available at : http://www.jetir.org/papers/JETIR2406658.pdf