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.

• Type: Conference
• Year: 2006
• Where: ACIVS
• Authors: Bahman Zafarifar, Peter H. N. de With
• Keywords: ACIVS 2006, Algorithm, Computer Vision, Pixel-accurate Sky Probability, Sky Areas