Description

ABSTRACT

Histogram equalization (HE), a simple contrast enhancement (CE) method, tends to show excessive enhancement and gives unnatural artifacts on images with high peaks in their histograms. Histogram-based CE methods have been proposed in order to overcome the drawback of HE, however, they do not always give good enhancement results. In this letter, a histogram-based locality-preserving CE method is proposed. The proposed method is formulated as an optimization problem to preserve localities of the histogram for performing image CE. The locality-preserving property makes the histogram shape of the enhanced image to be similar to that of the original image. Experimental results show that the proposed histogram-based method gives output images with graceful CE on which existing methods give unnatural results.

EXISTING METHOD

• Histogram Equalization(HE)
• Brightness Preserving Bi-HE (BBHE)
• Minimum Mean Brightness Error BHE (MMBEBHE)
• Brightness Preserving Dynamic HE(BPDHE)
• Cascaded Multistep Binomial Filtering HE (CMBFHE)
• Recursively Separated And Weighted Histogram Equalization (RSWHE)

DRAWBACKS

• Image Contrast is Very Less
• Computational Complexity is Very High
• Computationally Expensive is More

PROPOSED METHOD

• Histogram-Based Locality- Preserving

BLOCK DIAGRAM

METHODOLOGIES

• Median Filter Process
• Histogram-Based Locality- Preserving
• Pixel NN Based Contract Enhancement
• Parameter Analysis

ADVANTAGES

• Image Contrast or Visibility is Very High
• Computational Complexity is Very Less
• Computationally Expensive is Less

APPLICATIONS

• Satellite Image
• Bio-Medical
• Digital Photograph (Multimedia)

SOFTWARE REQUIREMENT

• MATLAB 7.8 or above versions

RESULTS

REFERENCES

[1] R. C. Gonzalez and R. E. Woods, Digital Image Processing, 3rd ed. Upper Saddle River, NJ: Pearson Education, 2010.

[2] Y. T. Kim, “Contrast enhancement using brightness preserving bi-histogram equalization,” IEEE Trans. Consumer Electron., vol. 43, no. 1, pp. 1–8, Feb. 1997.

[3] S.-D. Chen and A. R. Ramli, “Minimum mean brightness error bi-histogram equalization in contrast enhancement,” IEEE Trans. Consumer Electron., vol. 49, no. 4, pp. 1310–1319, Nov. 2003.

[4] H. Ibrahim and N. S. P. Kong, “Brightness preserving dynamic histogram equalization for image contrast enhancement,” IEEE Trans. Consumer Electron., vol. 53, no. 4, pp. 1752–1758, Nov. 2007.

[5] S.-D. Chen and A. Ramli, “Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation,” IEEE Trans. Consumer Electron., vol. 49, no. 4, pp. 1301–1309, Nov. 2003.

[6] D. Menotti, L. Najman, J. Facon, and A. A. Araujo, “Multi-histogram equalization methods for contrast enhancement and brightness preserving,” IEEE Trans. Consumer Electron., vol. 53, no. 3, pp. 1186–1194, Aug. 2007.