1. Vaishali R, Nancy Kuchhal
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal
Dr V Madhu Viswanatham (Guide) School of Computing Science and Engineering VIT University, Vellore, India

2. 1
ABSTRACT
The reduction of unwanted noise contamination is required to improve the accuracy of analysis in any field that finds application with signals. In this paper we compare various Gaussian filters on Gray scale and medical images that are corrupted by various noise mixtures. we test them using noise ratio calculation formula (PSNR) and image experts for their quality analysis and propose a hybrid bilateral filter by the combination of switching bilateral filter and low pass Gaussian filters. We have achieved less amount of noise reduction but the visibility obtained while testing by the image experts and edge detection operators have proven it to be a good filter against the noise mixture contamination.
Keywords— noise filtering , mixed noise, hybrid bilateral filter, Edge Detection and image enhancement
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

3. Input Image = Actual Image + Mixed Noise2
INTRODUCTION
Images are reliable resources for clinical diagnosis.The common noise forms that contaminate the image signals are Gaussian noise (otherwise known as distributed noise), salt & pepper noise (otherwise called impulse noise) , poisson noise and speckle noise (or multiplicative noise) [1-2]. We aim to denoise the mixed noise contamination from the corrupted image Signal
Input Image = Actual Image + Mixed Noise
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

4. Poisson Noise Speckle Noise Gaussian Noise Salt & Pepper Noise3
NOISE MODELS
Poisson Noise
Speckle Noise
Gaussian Noise
Salt & Pepper Noise
All these noises are added to the input Image and the denoising algorithms are applied over them.
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

5. INPUT DATA FOR ANALYSIS4
INPUT DATA FOR ANALYSIS
Input Image (Above) after Mixed noise contamination (Below) C A B D
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

6. FILTER ANALYSIS OVER NOISY IMAGE5
FILTER ANALYSIS OVER NOISY IMAGE
Peak- Signal Noise Ratio, tabulated analysing the output filtered image with input noisy image
Filters
Img A
Img B
Img C
Img D
High pass
Low Pass
Bilateral
Fast Bilateral
Imp.Switchable
Hybrid
Original
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

7. FILTER ANALYSIS OVER NOISY IMAGE6
FILTER ANALYSIS OVER NOISY IMAGE
Decision Taken by the image experts over the filtered output image.
In image expert quality prediction over the resultant images, we tabular the data of analysis as V- Visible, B- Blurred , N- Noisy,NV- noisy and Visible, NB- noisy Blurred and VB - Visible Blurred. A B C D
Highpass N
Lowpass
Bilateral NV
Fast shift VB
Improved Switch NB
Hybrid V
Input Img
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

8. QUALITY ANALYSIS OVER NOISY IMAGE7
QUALITY ANALYSIS OVER NOISY IMAGE
(i) Noise Ratio detection
PSNR is obtained by the calculating the result by implementing the formula [11].
P= 10* log10(m*n*peak2 /sum(sum(B- A) 2)) db
(ii) Image expert judgement
In image expert quality prediction over the resultant images, we tabular the data of analysis as
V- Visible, B- Blurred , N- Noisy,NV- noisy and Visible, NB- noisy Blurred and VB - Visible Blurred.
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

9. IMAGE VISIBILITY ANALYSIS (noisy vs filtered) GAUSSIAN HIGH PASS8
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

10. IMAGE VISIBILITY ANALYSIS (noisy vs filtered) GAUSSIAN LOW PASS9
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

11. IMAGE VISIBILITY ANALYSIS (noisy vs filtered) GAUSSIAN LOW PASS10
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

12. IMAGE VISIBILITY ANALYSIS (noisy vs filtered) BILATERAL FILTER11
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

13. IMAGE VISIBILITY ANALYSIS (noisy vs filtered)
FAST SHIFT BILATERAL FILTER 12
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

14. IMAGE VISIBILITY ANALYSIS (noisy vs filtered)
IMP SWITCHABLE BILATERAL FILTER 13
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

15. IMAGE VISIBILITY ANALYSIS (noisy vs filtered)
PROPOSED HYBRID BILATERAL FILTER 14
Enhancement of Medical and Gray scale images using Gaussian Filters and Edge detection operators
Vaishali R, Nancy Kuchhal and Dr V Madhu Viswanatham (Guide)School of Computing Science and Engineering, VIT University

16. EDGE DETECTION OPERATORS15
Edge Preservation test
The main objective of filtering is to retain the edge features even after filtering. We apply five distinctive edge detection operators over our experimental result images and find which filtering produces best output tabulated in table (v). They are named as Sobel operator , Prewitt operator, Canny operator, Roberts operator and Log edge detection operations decision on visibility and Edge detection operators output, We arrive at a decision that the Hybrid Bilateral filter proposed, work efficiently on all the images to produce good quality of visibility by filtering the noise mixture contaminated images, compared to other filters, in spite of the noise levels.

17. EDGE DETECTION OPERATORS16 1 c d a b e 2
A. Canny
B. Roberts
C. Prewitt
D. Sobel
E. Log
1. Prop. Hybrid Bilateral (best visibility)
2. Low pass gaussian (lowest PSNR)

18. CONCLUSION & RESULT 17
We arrive at a decision that the Hybrid Bilateral filter proposed, work efficiently on all the images to produce good quality of visibility by filtering the noise mixture contaminated images, compared to other filters, in spite of the noise levels.

19. [16] Suraj Kamya, Mathworks (2014)
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bcentral/fileexchange/ highdensity-bilateral-filter
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med/ckb/infectious_diseases/ jpg

20. Vaishali R, Nancy Kuchhal
THANK YOU!
Vaishali R, Nancy Kuchhal
Dr V Madhu Viswanatham (Guide) School of Computing Science and Engineering VIT University