Enhanced low-light auto-focus system model in digital still and cell-phone cameras
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Adaptive variance based sharpness computation for low contrast images
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
A comparison of contrast measurements in passive autofocus systems for low contrast images
Multimedia Tools and Applications
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Images captured by a digital or cell-phone camera in low-light environments usually suffer from a lack of sharpness due to the failure of the camera's passive auto-focus (AF) system to locate the peak in-focus position of a sharpness function that is extracted from the image. In low-light, the sharpness function becomes flat, making it quite difficult to locate the peak.In this paper, a systematic approach is introduced to address the problem of low-light AF by performing computationally simple image enhancement preprocessing steps as part of the image pipeline. These enhancement steps elevate the sharpness function peak, leading to auto-focusing in low-light conditions. A sharpness junction quality measure along with experimental guidelines are presented for determining the most prominent enhancement steps for low-light AF. The implementation results on an actual digital camera platform are also shown to demonstrate the effectiveness of our solution.