Research Paper | Electronics & Communication Engineering | India | Volume 5 Issue 11, November 2016
Adaptive Contrast Enhancement and White Balancing Integration for Image Enhancement Based on Non-linear Generalized Equalization Model
Chiruvella Suresh | K. Amith Bansal
Abstract: The digital image processing has introduced revolutionary developments in research fields like medicine, military, security, biometrics, robotics, satellite image processing, digital image compression, digital image enhancement, digital video processing, etc. Image enhancement is the predominant fundamental step in the image processing and digital image enhancement creates an image which is perceived by human visual system (HVS) in pleasant way. Although tremendous progress has been made in the past years on digital image enhancement process but still digital image enhancement is area of concern in the field of digital image processing. In the proposed method a non-linear generalized equalization model for image enhancement has proposed by integrating the non linear contrast enhancement and white balancing to form a unified algorithm based on the different parameter configurations into considerations. An adaptive image enhancement algorithm has been derived which yields good theoretical results based on two important histogram transform properties namely contrast gain and non linearity. Finally experimental results shows proposed method achieves good performance and low complexity over traditional state of art methods and proposed model is successful in achieving better efficiency in terms of tone correction as well as white balancing.
Keywords: Image enhancement, white balancing, non-linear contrast enhancement, transformation, non linearity
Edition: Volume 5 Issue 11, November 2016,
Pages: 447 - 452
How to Cite this Article?
Chiruvella Suresh, K. Amith Bansal, "Adaptive Contrast Enhancement and White Balancing Integration for Image Enhancement Based on Non-linear Generalized Equalization Model", International Journal of Science and Research (IJSR), Volume 5 Issue 11, November 2016, pp. 447-452, https://www.ijsr.net/get_abstract.php?paper_id=ART20162823
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