An Adaptive Markov Random Field for Structured Compressive Sensing
نویسندگان
چکیده
منابع مشابه
Compressive Sensing and Structured Random Matrices
These notes give a mathematical introduction to compressive sensing focusing on recovery using `1-minimization and structured random matrices. An emphasis is put on techniques for proving probabilistic estimates for condition numbers of structured random matrices. Estimates of this type are key to providing conditions that ensure exact or approximate recovery of sparse vectors using `1-minimiza...
متن کاملLight Field Compressive Sensing
This paper presents a novel approach to capture light field in camera arrays based on the compressive sensing framework. Light fields are captured by a linear array of cameras with overlapping field of view. In this work, we design a redundant dictionary to exploit cross-cameras correlated structures in order to sparsely represent cameras image. We show experimentally that the projection of com...
متن کاملCompressive Sensing by Random Convolution
This paper demonstrates that convolution with random waveform followed by random time-domain subsampling is a universally efficient compressive sensing strategy. We show that an n-dimensional signal which is S-sparse in any fixed orthonormal representation can be recovered from m & S log n samples from its convolution with a pulse whose Fourier transform has unit magnitude and random phase at a...
متن کاملStructured sublinear compressive sensing via belief propagation
Compressive sensing (CS) is a sampling technique designed for reducing the complexity of sparse data acquisition. One of the major obstacles for practical deployment of CS techniques is the signal reconstruction time and the high storage cost of random sensing matrices. We propose a new structured compressive sensing scheme, based on codes of graphs, that allows for a joint design of structured...
متن کاملCluster-Based Image Segmentation Using Fuzzy Markov Random Field
Image segmentation is an important task in image processing and computer vision which attract many researchers attention. There are a couple of information sets pixels in an image: statistical and structural information which refer to the feature value of pixel data and local correlation of pixel data, respectively. Markov random field (MRF) is a tool for modeling statistical and structural inf...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Image Processing
سال: 2019
ISSN: 1057-7149,1941-0042
DOI: 10.1109/tip.2018.2878294