With the increase in the number of digital images, the demand for pleasing and accurate images is increasing. However, the images captured by modern cameras get degraded by noise. Noise in an image is a distortion of colour information in images. Noise is the term to coin digital distortion. The image turns out to be noisier when captured at night. The case study attempts to build a predictive model which takes the noisy image as input and outputs its denoised counterpart.
This problem is based on Computer Vision. Advancements in Deep Learning like CNNs have been able to provide State-of-the-Art performance in Image Denoising. The model used to perform Image Denoising is DnCNN (Denoising Convolutional Neural Networks).
Both BSD300 and BSD500 datasets were used as training data. BSD68 was used for validation data.