Embedding data and task parallelism in image processing applications

TL;DR: This book presents an overview of the guidelines and strategies for transitioning an image or video processing algorithm from a research environment into a real-time constrained environment, consisting of algorithm simplifications, hardware architectures, and software methods.

TL;DR: This research tried to describe the role of parallel image processing in the field of medical imaging and discussed the problems encountered to implement parallel computing in various image processing applications.

TL;DR: A simple, efficient, finite state machine-based approach for communication minimization of library-based data parallel regular domain problems, referred to as lazy parallelization, where a sequential program is parallelized automatically at runtime by inserting communication primitives and memory management operations whenever necessary.

TL;DR: Analysis of parallel and distributed image processing with comprehensive details is presented with emphasis on mechanisms, tools/technology/API used, application domains, and ongoing research work to provide concise understanding to beginners.

TL;DR: In this paper, a method for finding the optical flow pattern is presented which assumes that the apparent velocity of the brightness pattern varies smoothly almost everywhere in the image, and an iterative implementation is shown which successfully computes the Optical Flow for a number of synthetic image sequences.

TL;DR: An iterative implementation is shown which successfully computes the optical flow for a number of synthetic image sequences and is robust in that it can handle image sequences that are quantified rather coarsely in space and time.

TL;DR: A fast and flexible algorithm for computing watersheds in digital gray-scale images is introduced, based on an immersion process analogy, which is reported to be faster than any other watershed algorithm.

TL;DR: In this paper, Fourier transform is used for spectral analysis of periodical signals and some properties of the spectrum are analyzed, and it is demonstrated that the spectrum is strongly depended of signal duration.