This document discusses medical image enhancement using histogram processing. A group of students aimed to improve features and characteristics of medical images for accurate diagnosis. They explored techniques like brightness preserving bi-histogram equalization and contrast limited adaptive histogram equalization. The group analyzed literature on histogram equalization methods and their ability to boost image contrast while preserving edges. They implemented various techniques in Matlab and tested them on medical images to generate enhanced results for better diagnosis.

1. Medical Image EnhancementMedical Image Enhancement
Using Histogram ProcessingUsing Histogram Processing
Group No. 19Group No. 19
Prashant Sharma (131042)Prashant Sharma (131042)
Prashant Upadhaya (131043)Prashant Upadhaya (131043)
Ajeet Meena (121009)Ajeet Meena (121009)
JAYPEE UNIVERSITY OF ENGINEERING AND TECHNOLOGY
Guna (M.P.)

2. • Medical Images are low contrast Images.
• Enhancement is needed to extract useful
information from them.
• Better characteristics of medical images for a right
diagnosis.

3. •Undertaking a challenging project in an interesting
area of research.
•Beneficial for biomedical application.
•Goals-improve features and gain better characteristic
for right diagnosis.
•For the welfare of society.
MOTIVATIONMOTIVATION

6. • YEONG-TAEG KIM (1997)- “Brightness preserving Bi-
Histogram Equalization”
• Drawback -Brightness of an image changes after the
histogram equalization.
• Overcome- Brightness preserving Bi-Histogram
Equalization

7. •J. Alex Stark (2000)- “Adaptive Image Contrast
Enhancement Using Generalizations of Histogram
Equalization”.
•Scheme for adaptive image contrast enhancement
based on a generalization of histogram equalization.
•Key feature-Cumulation Function

8. • Sukhjinder Singh, R.K. Bansal and Savina Bansal
(2012)-”MEDICAL IMAGE ENHANCEMENT USING
HISTOGRAM PROCESSING TECHNIQUES FOLLOWED BY
MEDIAN FILTER “
• To enhance the image Global Histogram Equalization
(GHE), Local Histogram Equalization (LHE) techniques are
used.
• Limitation-Unpleasant visual artifact
• Overcome-Brightness Preserving Bi-Histogram Equalization
(BBHE) and Dualistic Sub-Image Histogram Equalization
(DSIHE).

9. • Dr. A. Sri Krishna , G. Srinivasa Rao and M. Sravya
(2013)-”CONTRAST ENHANCEMENT TECHNIQUES USING
HISTOGRAM EQUALIZATION METHODS”
• Limitation-Preserve brightness on the output but does not
have a natural look.
• Overcome-Multi-HE

10. • Monali Pancha(2016)-”Contrast Enhancement Techniques
to Improve the Quality of Medical Images”
• Visual examination of medical images is essential in the
diagnosis of many diseases.
• Review of techniques and application.

11. • Kulwinder Kaur, Er. Inderpreet Kaur, Er. Jaspreet (2016)-”A
Survey on Image Enhancement by Histogram equalization
Methods”
•Study of various techniques of histogram equalization.
•Brightness Preserving Dynamic Histogram Equalization,
Recursive Mean–Separate Histogram Equalization, Mean
Brightness Preserving Histogram Equalization, etc.

12. •Sargun and Shashi B. Rana (2016)-A Review of Medical
Image Enhancement Techniques for Image Processing
•Review about the techniques of medical image
enhancement
•Detailed review-Histogram Equalization, Adaptive
Histogram Equalization ,(BBHE) ,Contrast limited adaptive
histogram equalization

13.  Ability to boost the contrast in digital images in efficient manner
by utilizing the edge preserving fuzzy filter hypothesis.
 Edge preserving fuzzy has ability to reduce the effectuation of
noise and yes it preserves the edges in efficient manner.
 Histogram Modified Contrast Limited Adaptive
Histogram Equalization (HM CLAHE) can be used to generate
better result.

14. 2016 2016Jul Aug Sep Oct Nov Dec
Topic
Finalization
Problem
analysis Solution
Design &
formulation
Theoretical
Analysis
Final Design
to Implement
Literature
Survey

15. 2017 2017Jan Feb Mar Apr May Jun
Matlab
Implementation
Result
Gathering
Comparison With
previous result
Fault
Detection
Fault
Rectification
and final
testing
Testing with
different
medical images

16. [1] YEONG-TAEG KIM (1997) “Contrast Enhancement Using Brightness
Preserving Bi-Histogram Equalization”
[2] J. Alex Stark (2000) “Adaptive Image Contrast Enhancement Using
Generalizations of Histogram Equalization”
[3] Sukhjinder Singh et.al “Medical Image Enhancement Using Histogram
Processing Techniques Followed by Median Filter”
[4] Dr. A. Sri Krishna , G. Srinivasa Rao and M. Sravya (2013)-”Contrast
enhancement technique using histogram equalizatiom method”
[5] Monali Pancha(2016)-”Contrast Enhancement Techniques to Improve the
Quality of Medical Images”
[6] Kulwinder Kaur, Er. Inderpreet Kaur, Er. Jaspreet (2016)-”A Survey on Image
Enhancement by Histogram equalization Methods”
[7] Sargun and Shashi B. Rana (2016)-”A Review of Medical Image Enhancement
Techniques for Image Processing”
[8] Gonzalez, Rafael C.(2009) “Digital image processing. Pearson Education
India”