A framework for real-time adaptive delivery of web images to resource-constrained devices is presented, bringing together techniques from image analysis, compression, rate-distortion optimization, and user interaction. Two fundamental themes in this work are: (1) a structured and scalable representation, obtained through content- and lower-level image analysis, that allows multiple descriptions of object regions, and (2) resource-optimized content adaptation in real time, facilitated by an algorithm for directly merging LZ77-compressed streams without the need for additional string matching.
Also introduced is a new distortion measure for image approximations based on a feature space distance. Using this measure, a color reduction algorithm is proposed. Simulation studies show that this algorithm can yield better results than previous approaches, both from a visual standpoint and in terms of feature space distortion.
The concentric mosaics offer a quick solution to the construction and navigation of a virtual environment. To reduce the vast data amount of the concentric mosaics, a compression scheme based on 3D wavelet transform has been proposed in a previous paper. In this work, we investigate the efficient implementation of the renderer. It is preferable not to expand the compressed bitstream as a whole, so that the memory consumption of the renderer can be reduced. Instead, only the data necessary to render the current view are accessed and decoded. The progressive inverse wavelet synthesis (PIWS) algorithm is proposed to provide the random data access and to reduce the calculation for the data access requests to a minimum. A mixed cache is used in PIWS, where the entropy decoded wavelet coefficient, intermediate result of lifting and fully synthesized pixel are all stored at the same memory unit because of the in- place calculation property of the lifting implementation. PIWS operates with a finite state machine, where each memory unit is attached with a state to indicate what type of content is currently stored. The computational saving achieved by PIWS is demonstrated with extensive experiment results.
As a new scene representation scheme, the concentric mosaic offers a quick way to capture and model a realistic 3D environment. This is achieved by shooting a lot of photos of the scene. Novel views can be rendered by patching vertical slits of the captured shots. The data amount in the concentric mosaic is huge. In this work, we compress the concentric mosaic image array with a 3D wavelet scheme. The proposed scheme first aligns the mosaic images, and then applies a 3D wavelet transform on the aligned mosaic image array. After that, the wavelet coefficients in each subband are split into cubes, where each of the cubes is encoded independently with an embedded block coder. Various cube bitstreams are then assembled to form the final compressed bitstream. Experimental result shows that the proposed 3D wavelet coder achieves a good compression performance.
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