This paper describes a new fade and dissolve detection methodology that utilizes wavelet transformation. This approach takes advantage of the production aspects of video as well as mimicking human perception. Each frame of the video is first decomposed into low-resolution component and high- resolution component using wavelet transformation. The possible gradual changes are first detected with edge spectrum average (ESA) feature which is obtained from the high- resolution component, in the mean time, the changing statistics of the ESA is studied to identify fades. Double chromatic difference is applied later on the low-resolution component to identify the dissolve transitions.
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