Improved Image Denoising Methodology using Deep CNN Bilateral Filter Compared to Additional Methods
Pallavi Bora1, Kapil Chaudhary2

1Pallavi Bora*, M-Tech Scholar, Department of Computer Science and Engineering, B.T.K.I.T. Dwarahat, Almora (Uttarakhand), India.
2Dr. Kapil Chaudhary, Assistant Professor, Department of Computer Science and Engineering, B.T.K.I.T. Dwarahat, Almora (Uttarakhand), India.

Manuscript received on March 28, 2021. | Revised Manuscript received on June 09, 2021. | Manuscript published on June 30, 2021. | PP: 191-196 | Volume-10 Issue-5, June 2021. | Retrieval Number:  100.1/ijeat.D23720410421 | DOI: 10.35940/ijeat.D2372.0610521
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Abstract: 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. ECNDNet (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. 
Keywords: Image Denoising, PSNR, Bilateral filter, CNN