Robust automatic focus algorithm for low contrast images using a new contrast measure
Low contrast images, suffering from a lack of sharpness, are easily influenced by noise. As a
result, many local false peaks may be generated in contrast measurements, making it
difficult for the camera's passive auto-focus system to perform its function of locating the
focused peak. In this paper, a new passive auto-focus algorithm is proposed to address this
problem. First, a noise reduction preprocessing is introduced to make our algorithm robust to
both additive noise and multiplicative noise. Then, a new contrast measure is presented to …
result, many local false peaks may be generated in contrast measurements, making it
difficult for the camera's passive auto-focus system to perform its function of locating the
focused peak. In this paper, a new passive auto-focus algorithm is proposed to address this
problem. First, a noise reduction preprocessing is introduced to make our algorithm robust to
both additive noise and multiplicative noise. Then, a new contrast measure is presented to …
Low contrast images, suffering from a lack of sharpness, are easily influenced by noise. As a result, many local false peaks may be generated in contrast measurements, making it difficult for the camera’s passive auto-focus system to perform its function of locating the focused peak. In this paper, a new passive auto-focus algorithm is proposed to address this problem. First, a noise reduction preprocessing is introduced to make our algorithm robust to both additive noise and multiplicative noise. Then, a new contrast measure is presented to bring in local false peaks, ensuring the presence of a well defined focused peak. In order to gauge the performance of our algorithm, a modified peak search algorithm is used in the experiments. The experimental results from an actual digital camera validate the effectiveness of our proposed algorithm.
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