V
Vladan Velisavljevic
Researcher at University of Bedfordshire
Publications - 72
Citations - 1352
Vladan Velisavljevic is an academic researcher from University of Bedfordshire. The author has contributed to research in topics: Wavelet transform & Image compression. The author has an hindex of 18, co-authored 68 publications receiving 1267 citations. Previous affiliations of Vladan Velisavljevic include Technical University of Berlin & École Polytechnique Fédérale de Lausanne.
Papers
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Directionlets: anisotropic multidirectional representation with separable filtering
TL;DR: This work presents a new lattice-based perfect reconstruction and critically sampled anisotropic M-DIR WT, which provides an efficient tool for nonlinear approximation of images, achieving the approximation power O(N/sup -1.55/), which, while slower than the optimal rate O-2/, is much better than O-1/ achieved with wavelets, but at similar complexity.
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On Dependent Bit Allocation for Multiview Image Coding With Depth-Image-Based Rendering
TL;DR: This paper derives a cubic distortion model based on basic DIBR properties, whose parameters are obtained using only a small number of viewpoint samples, and demonstrates that the optimal selection of coded views and quantization levels for corresponding texture and depth maps is equivalent to the shortest path in a specially constructed 3-D trellis.
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Space-Frequency Quantization for Image Compression With Directionlets
TL;DR: This paper shows how to design and implement a novel efficient space-frequency quantization (SFQ) compression algorithm using directionlets and shows that the new compression method outperforms the standard SFQ in a rate-distortion sense, both in terms of mean-square error and visual quality, especially in the low-rate compression regime.
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Light field geometry of a standard plenoptic camera
TL;DR: This research provides an approach to estimate the distance and depth of refocused images extracted from captures obtained by an SPC, and a ray tracing model employing linear equations has been developed and implemented using Matlab.
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Refocusing distance of a standard plenoptic camera.
TL;DR: The proposed refocusing estimator assists in predicting object distances just as in the prototyping stage of plenoptic cameras and will be an essential feature in applications demanding high precision in synthetic focus or where depth map recovery is done by analyzing a stack of refocused photographs.