Blue Sky Detection for Picture Quality Enhancement
Content analysis of video and still images is attractive for multiple reasons, such as enabling content-based actions and image manipulation. This paper presents a new algorithm and feature model for blue-sky detection. The algorithm classifies the sky areas by computing a pixel-accurate sky probability. Such a probabilistic measure matches well with the requirements of typical video enhancement functions in TVs. This algorithm enables not only content-adaptive picture quality improvement, but also more advanced applications such as content-based annotation of, and retrieval from image and video databases. When compared to existing algorithms, our proposal shows considerable improvements in correct detection/rejection rate of sky areas, and an improved consistency of the segmentation results.
KeywordsFalse Detection Color Model Correct Rejection Video Application Picture Quality
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