Enhancing the Quality of Underwater Images using Fusion of sequential Filters and Dehazing

Effectively analyzing underwater images and identifying any object under the water has become a difficult task. Generally, the factors affecting underwater images are uneven lighting, low contrast, blunt colors, and characteristics of an object based on absorption and scattering of light. The proposed technique involves applying white balancing and contrast enhancement to the original image. The combination of filters namely homomorphic filtering, wavelet denoising, bilateral filter , adaptive filters are used and applied sequentially on the degraded underwater images. The results obtained showed that the proposed algorithm works well in refining the underwater image attributes. Peak Signal to Noise Ratio (PSNR) and Mean Squared Error (MSE) are used to evaluate performance of the algorithm.