Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
We describe approximate digital implementations of two new mathematical transforms, namely, the ridgelet transform [3] and the curvelet transform [7, 6]. Our implementations offer...
Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...
Multiplicative noise (also known as speckle noise) models are central to the study of coherent imaging systems, such as synthetic aperture radar and sonar, and ultrasound and laser...
We describe and compare three probabilistic ways to perform Content Based Image Retrieval (CBIR) in compressed domain using images in JPEG2000 format. Our main focus are arbitrary ...