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Vol. 161, Issue 12, December 2013, pp. 114-120

 

Bullet

 

Under-Exposed Image Enhancement Based on Relaxed Luminance Optimization
 
1 Chunxiao LIU, 2 Feng YANG

1 School of Computer Science & Information Engineering, Zhejiang Gongshang University, Hangzhou, 310018, China

2 College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China

1 Tel.: +86-571-28008289
E-mail: cxliu@mail.zjgsu.edu.cn

 

Received: 23 September 2013   /Accepted: 22 November 2013   /Published: 30 December 2013

Digital Sensors and Sensor Sysstems

 

Abstract: In order to overcome the dimming and blurring effect resulted from deficient enhancement or the haloing and noising problem caused by excessive enhancement, this paper proposes a luminance optimization based under-exposed image clearness enhancement algorithm, which treats it as the simultaneous augmentation of luminance and contrast, and combines them in an optimization framework under the expectations of augmented luminance and gradient fields. We adopt a relaxation strategy in the gradient energy terms of the framework to further suppress the noise amplification phenomenon. Experimental results demonstrate that our algorithm is simple and flexible, and obtains clear pictures for both locally and globally under-exposed images at the cost of only solving a system of sparse linear equations.

 

Keywords: Under-exposed image enhancement, Luminance optimization, Relaxation strategy.

 

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