Wavelet transform has become a very powerful tool for image/video compression and processing. In this dissertation we present our research in the area of three-dimensional (3-D) wavelet based video compression and Gabor wavelet based video object tracking, respectively.
The wavelet transform has been successfully used for image compression. Its success in image compression motivates a lot of researches in the wavelet transform based video compression. 3-D wavelet transform based video compression is a direction drawing many attentions. We investigates two topics in this area.
The first topic is optimal 3-D zerotree (ZTR) structure for the 3-D wavelet based video compression. Many researches have been done to use the 3-D zerotree and 3-D wavelet transform in video compression. However, the problem of how to build a 3-D zerotree was not studied carefully. In this research, we study the theory behind building a zerotree and propose a new 3-D zerotree structure which generates better coding performance.
The second topic is time and space efficiency of the 3-D wavelet transform based video compression for real time video applications. The 3D wavelet transform needs to save and process large 3-D data which is a bottle neck for real time applications. We investigate this issue and present a time and space efficient video codec utilizing integer wavelet transforms.
The wavelet transform can represent signal in a multi-resolution way so it is also used in object tracking. We presents an object tracking method for object-based video processing which uses a 2-D Gabor wavelet transform (GWT), a 2-D triangular mesh and a 2-D golden section algorithm. The feature points are stochastically selected based on the energy of their GWT coefficients. The global placement of the feature points is determined by a 2-D mesh whose feature is the area of the triangles formed by the feature points. In order to find the corresponding object in the next frame, the 2-D golden section algorithm is employed, and this can be shown to be the fastest algorithm to find the maximum of a unimodal function.