Open AccessBook
Fundamentals of digital image processing
Anil K. Jain
- 03 Oct 1988
8.9K
TL;DR: This chapter discusses two Dimensional Systems and Mathematical Preliminaries and their applications in Image Analysis and Computer Vision, as well as image reconstruction from Projections and image enhancement.
read more
Abstract: Introduction. 1. Two Dimensional Systems and Mathematical Preliminaries. 2. Image Perception. 3. Image Sampling and Quantization. 4. Image Transforms. 5. Image Representation by Stochastic Models. 6. Image Enhancement. 7. Image Filtering and Restoration. 8. Image Analysis and Computer Vision. 9. Image Reconstruction From Projections. 10. Image Data Compression.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Machine Learning Analysis for Quantitative Discrimination of Dried Blood Droplets
Lama Hamadeh,Samia Imran,Martin Bencsik,Graham R. Sharpe,Michael A. Johnson,David J. Fairhurst +5 more
TL;DR: Evidence that images of dried blood droplets have a signature revealing the exhaustion level of the person is presented, and an entirely novel approach to studying human dried blood Droplet patterns is disclosed, which can be applied to identify diseases.
Contrast enhancement of noisy low-light images based on structure-texture-noise decomposition
TL;DR: Experimental results demonstrate that the proposed STN algorithm sharpens the texture and enhances the contrast more effectively than conventional algorithms, while providing robust performance under various noise and illumination conditions.
51
The past, present, and future of image and multidimensional signal processing
TL;DR: The field of image and multidimensional signal processing began as a field of strong theoretical framework based on mathematics, statistics, and physics as mentioned in this paper, and with advances in computing, memory and image-sensing technology, techniques developed for image enhancement, still and moving image compression, image understanding gave this field a solid base of practical applications.
51
Moment based texture segmentation
Mihran Tuceryan
- 30 Aug 1992
TL;DR: The moment based texture segmentation algorithm has successfully segmented binary images containing textures with identical second-order statistics as well as a number of natural gray level texture images.
Motion Estimation Methods for Video Compression—A Review
TL;DR: This paper focuses on motion estimation and compensation techniques as tools that are used in video compression applications.
51
References
A New Approach to Linear Filtering and Prediction Problems
Tamer Basar
- 01 Jan 2001
TL;DR: In this paper, the clssical filleting and prediclion problem is re-examined using the Bode-Shannon representation of random processes and the?stat-tran-sition? method of analysis of dynamic systems.
22.7K
Linear prediction: A tutorial review
John Makhoul
- 01 Apr 1975
TL;DR: This paper gives an exposition of linear prediction in the analysis of discrete signals as a linear combination of its past values and present and past values of a hypothetical input to a system whose output is the given signal.
4.4K
•Proceedings Article
Image Processing
E.E. Pissaloux
- 01 Jan 1994
TL;DR: The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images.
2.5K