An improved image contrast enhancement in multiple-peak images based on histogram equalization

The histogram equalization (HE) is one of the most popular methods for image contrast enhancement. However, HE algorithm has two main disadvantages. To solve these problems, this paper presents an improved image contrast enhancement based on histogram equalization, which is especially suitable for multiple-peak images. Firstly, the input image is convolved by a Gaussian filter with optimum parameters. Secondly, the original histogram can be divided into different areas by the valley values of the image histogram. Thirdly, using of our proposed method processes images. This method outperforms others on the aspects of simplicity and adaptability. We have applied the proposed algorithm on a database which includes 160 normal images and compared our proposed method with HE and BHE. The result demonstrates that the proposed algorithm has good performance in the field of image enhancement. This method can also be realized by simple hardware and consumer electronics, efficiently.

[1]  Abdul Wahab Abdul Rahman.  Novel approach to automated fingerprint recognition , 1998 .

[2]  José L. Pérez-Córdoba,et al.  Histogram equalization of speech representation for robust speech recognition , 2005, IEEE Transactions on Speech and Audio Processing.

[3]  Bingjian Wang,et al.  A real-time contrast enhancement algorithm for infrared images based on plateau histogram , 2006 .

[4]  Yeong-Taeg Kim,et al.  Quantized bi-histogram equalization , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[5]  Phan Tran Ho Truc,et al.  Vessel Enhancement Using Directional Features , 2007 .

[6]  Abdul Wahab,et al.  Novel approach to automated fingerprint recognition , 1998 .

[7]  Josef Bigün,et al.  Local Features for Enhancement and Minutiae Extraction in Fingerprints , 2008, IEEE Transactions on Image Processing.

[8]  Soo-Chang Pei,et al.  Virtual restoration of ancient Chinese paintings using color contrast enhancement and lacuna texture synthesis , 2004, IEEE Transactions on Image Processing.

[9]  Heung-Kook Choi,et al.  Brightness preserving weight clustering histogram equalization , 2008, IEEE Transactions on Consumer Electronics.

[10]  Hu Min.  Local Histogram Equalization with Brightness Preservation , 2006 .

[11]  Haidi Ibrahim,et al.  Image sharpening using sub-regions histogram equalization , 2009, IEEE Transactions on Consumer Electronics.

[12]  John Q. Gan,et al.  Interactive image enhancement by fuzzy relaxation , 2007, Int. J. Autom. Comput..

[13]  Karim Faez,et al.  A Novel Approach for Contrast Enhancement in Biomedical Images Based on Histogram Equalization , 2008, 2008 International Conference on BioMedical Engineering and Informatics.

[14]  Stephen M. Pizer,et al.  The Medical Image Display and Analysis Group at the University of North Carolina: Reminiscences and philosophy , 2003, IEEE Transactions on Medical Imaging.

[15]  Raimondo Schettini,et al.  Low-quality image enhancement using visual attention , 2007 .