C
Chandrajit Pal
Researcher at Information Technology University
Publications - 34
Citations - 250
Chandrajit Pal is an academic researcher from Information Technology University. The author has contributed to research in topics: Field-programmable gate array & Computer science. The author has an hindex of 8, co-authored 28 publications receiving 171 citations. Previous affiliations of Chandrajit Pal include Indian Institutes of Technology & University of Southampton.
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A Brief Survey of Recent Edge-Preserving Smoothing Algorithms on Digital Images.
TL;DR: This paper provides a concrete introduction to edge preserving filters starting from the heat diffusion equation in olden to recent eras, an overview of its numerous applications, as well as mathematical analysis, various efficient and optimized ways of implementation and their interrelationships.
Proceedings ArticleDOI
Architecture for complex network measures of brain connectivity
TL;DR: This is a first study on the implementation of the complex network topology parameters of brain connectivity measure which has been synthesized at 25 Mhz, using STMicroelectronics 130-nm technology library and having a dynamic power consumption of 10 nW, making it amenable for real-time high speed operations.
Journal ArticleDOI
Rician noise removal in magnitude MRI images using efficient anisotropic diffusion filtering
TL;DR: This article extends the work of the classical anisotropic diffusion filter and has customized it to remove Rician noise in the magnitude MRI image in 3D domain space and shows better results against various quality measures in terms of noise removal and edge preservation while retaining fine textures.
Journal ArticleDOI
An Efficient FPGA Implementation of Optimized Anisotropic Diffusion Filtering of Images
TL;DR: This paper presents the FPGA implementation of an edge-preserving anisotropic diffusion filter for digital images, which completely replaced the convolution operation and implemented the same using simple arithmetic subtraction of the neighboring intensities within a kernel.
Journal ArticleDOI
Shape and Positional Anisotropy Based Area Efficient Magnetic Quantum-Dot Cellular Automata Design Methodology for Full Adder Implementation
TL;DR: This letter proposes a design methodology and demonstrates the hybrid approach of using slant edged input and 45$^\circ$ aligned nanomagnets for optimized binary full adder design, leading to a area efficient architectural design.