Improved Wyner-Ziv video coding efficiency using bit plane prediction

The research work is partially funded by STEPS-Malta and partially by the European Union - ESF 1.25.Distributed Video Coding (DVC) is a coding paradigm where video statistics are exploited, partially or totally, at the decoder. The performance of such a codec depends on the accuracy of the soft-input information estimated at the decoder, which is affected by the quality of the side information (SI) and the dependency model. This paper studies the discrepancies between the bit planes of the Wyner-Ziv (WZ) frames and the corresponding bit planes of the SI. The relationship between these discrepancies is then exploited to predict the locations where the bit plane of the SI is expected to differ from that of the original WZ frame. This information is then used to derive more accurate soft-input values that achieve better compression efficiencies. Simulation results demonstrate that a WZ bit-rate reduction of 9.4% is achieved for a given video quality.peer-reviewe

Compact Rotation Invariant Image Descriptors By Spectral Trimming

Image descriptors are widely used in applications such as object recognition, pattern classification and image registration. The descriptors encode the local visual content of the image to provide a compact, robust and distinctive representation of objects. If images differ in orientation, descriptors must be rotation invariant. This paper introduces a compact rotation invariant descriptor. The approach is based on the representation of the local visual content by a graph. A function living on the graph vertices is evaluated and transformed through spectral trimming. This transform is rotation invariant and reduces the dimensionality of the descriptor. The performance of the introduced descriptor is as good as the SIFT descriptor performance, while being about ten times more compact, as shown by experiments on transmission electron microscope images