Image Denoising techniques are widely used to
remove the noise from the images. Due to the ease of the bilateral
filter, it is used very often to remove the noise from the images. In
this paper, a novel approach has been proposed to enhanced
bilateral filter in conjunction with CNN as a booster to eliminate
Gaussian noise from Grey images. Studies reveal that standard
CNN using a bilateral filter is the best technique to eliminate
Gaussian noise from images along with high PSNR values. This
paper also performs a comparative study of the various existing
techniques for image denoising with the CNN technique and the
applied Bilateral filter Method as a de facto to improve the results
in terms of enhanced PSNR values. ECND Net (Enhanced CNN)
applied to noisy images with standard deviation σ = 15 gives
PSNR values up to 32.81 In comparison to this when both
bilateral filter and deep CNN applied, in conjunction produces
improved PSNR values up to 34.73 along with the equivalent
standard deviation. The results in this work reveal better
performance in terms of PSNR as compared to other methods.
The test result proves that the bilateral filter Method along with
CNN can improve the quality of restored images significantly
better.
Iterative solvers for image denoising with diffusion models: A comparative study
