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2017 | OriginalPaper | Chapter

4. Image Enhancement

Author : Klaus D. Toennies

Published in: Guide to Medical Image Analysis

Publisher: Springer London

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Abstract

Two reasons exist for applying an image enhancement technique. Enhancement can increase perceptibility of objects in an image to the human observer or it may be needed as a preprocessing step for subsequent automatic image analysis. Enhancement methods differ for the two purposes. An enhancement method requires a criterion by which its success can be judged. This will be a definition of image quality, since improving quality is the goal of such method. Various quality definitions will be presented and discussed. Different enhancement techniques will be presented covering methods for contrast enhancement, for the enhancement of edges, and for noise reduction. Edge-preserving smoothing based on different assumptions about noise and edges in images will be presented in detail including the presentation of several popular methods for edge-preserving smoothing.

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previous chapter Image Storage and Transfer

next chapter Feature Detection

Compression rates of a lossless compression method using signal compression are bounded by the entropy. These methods compress pixels independent of their neighborhood. It can be shown that the maximum compression rate is the ratio of bits per pixel in the image to bits per pixel as predicted by entropy. Lossless compression using other kinds of methods such as run-length encoding may achieve higher compression rates.

The actual definition is a bit more complex. It essentially says that only those objects in two adjacent slices should overlap for which the shortest distance on the surface between any two points on the two slices should not intersect any other slices.

The Laplacian may also be computed as divergence of the gradient, denoted as ∇² = ∇·∇, hence the symbol ∇².

The reason for this is easily seen when the filter is transformed into the spatial domain in order to form the corresponding convolution kernel. The result is a sinc function which obviously causes the repetitions of edges after filtering, which is called ringing.

Al-Zubi S, Toennies KD, Bodammer N, Hinrichs H (2002). Fusing markov random fields with anatomical knowledge and shape based analysis to segment multiple sclerosis white matter lesions in magnetic resonance images of the brain. In: Proceedings of SPIE (medical imaging 2002), vol 4684, pp 206–215

Aurich V, Weule J (1995) Non-linear Gaussian filters performing edge preserving diffusion. Mustererkennung 1995:538–545

Baydush AH, Floyd CE (2000) Improved image quality in digital mammography with image processing. Med Phys 27(7):1503–1508CrossRef

Besag J (1986) On the statistical analysis of dirty pictures. J R Stat Soc Ser B (Methodological) 48(3):259–302MathSciNetMATH

Bouman CA, Shapiro M (1994) A multiscale random field model for Bayesian image segmentation. IEEE Trans Image Process 3(2):162–177CrossRef

Carmona R, Zhong S (1998) Adaptive smoothing respecting feature directions. IEEE Trans Image Process 7(3):353–358CrossRef

Chen (2005) Adaptive smoothing via contextual and local discontinuities. IEEE Trans Pattern Anal Mach Intell 27(10):1552–1567CrossRef

Dong C, Loy CC, He K, Tang X (2016) Image super-resolution using deep convolutional networks. IEEE Trans Pattern Anal Mach Intell 38(2):295–307CrossRef

Durand F, Dorsey J (2002) Fast bilateral filtering for the display of high-dynamic-range images. ACM Trans Graphics (TOG) 21(3):257–266CrossRef

Eisemann E, Durand F (2004) Flash photography enhancement via intrinsic relighting. ACM Trans Graphics (TOG) 23(3):673–678CrossRef

Elad M (2002) On the origin of the bilateral filter and ways to improve it. IEEE Trans Image Process 11(10):1141–1151MathSciNetCrossRef

Garnier SJ, Bilbro GL, Gault JW, Snyder WE (1995) Magnetic resonance image restoration. J Math Imaging Vis 5(1):7–19CrossRef

Geman S, Geman D (1984) Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Trans Pattern Anal Mach Intell 6(6):721–741CrossRefMATH

Geman D, Reynolds G (1992) Constrained restoration and the recovery of discontinuities. IEEE Trans Pattern Anal Mach Intell 14(3):367–383CrossRef

Haralick RM (1979) Statistical and structural approaches to texture. Proc IEEE 67(5):786–804CrossRef

He K, Sun J, Tang X (2010) Guided image filtering. Comput Vis—ECCV:11–14

Hu Y, Dennis TJ (1991). MAP estimation in image restoration by a local search enhanced genetic algorithm. In: 6th international conference on digital processing of signals in communications, pp 123–128

Hurn M, Jennison C (1996) An extension of Geman’s and Reynold’s approach to constrained restoration and the recovery of discontinuities. IEEE Trans Pattern Anal Mach Intell 18(6):657–662CrossRef

Johnson VE, Wong WH, Hu X, Chen CT (1991) Image restoration using Gibbs priors: boundary modeling, treatment of blurring, and selection of hyperparameters. IEEE Trans Pattern Anal Mach Intell 13(5):413–425CrossRef

Li HD, Kallergi M, Clarke LP, Jain VK, Clark RA (1995) Markov random field for tumor detection in digital mammography. IEEE Trans Med Imaging 14(3):565–576CrossRef

Loupas T, McDicken WN, Allan PL (1989) An adaptive weighted median filter for speckle suppression in medical ultrasonic images. IEEE Trans Circ Syst 36(1):129–135CrossRef

Marroquin JL, Vemuri BC, Botello S, Calderon E, Fernandez-Bouzas A (2002) An accurate and efficient Bayesian method for automatic segmentation of brain MRI. IEEE Trans Med Imaging 21(8):934–945CrossRefMATH

Oktay O, Bai W, Lee M, Guerrero R, Kamnitsas K, Cabellero J, Monteiro de Marvao AMS, Cook S, O’Regan D, Rueckert D (2016) Multi-input cardiac image super-resolution using convolutional neural networks. In: MICCAI 2016. Part III, LNCS, vol 9902, pp 246–254

Paris S, Durand F (2006). A fast approximation of the bilateral filter using a signal processing approach. Comput Vis—ECCV:568–580

Peli E (1990) Contrast in complex images. J Opt Soc America A 7(10):2032–2040CrossRef

Perona P, Malik J (1990) Scale-space and edge detection using anisotropic diffusion. IEEE Trans Pattern Anal Mach Intell 12(7):629–639CrossRef

Pham TQ, Van Vliet LJ (2005). Separable bilateral filtering for fast video preprocessing. In: IEEE international conference multimedia and expo, ICME 2005

Raya SP, Udupa JK (1990) Shape-based interpolation of multidimensional objects. IEEE Trans Med Imaging 9(1):32–42CrossRef

Saha PK, Udupa JK, Odhner D (2000) Scale-based fuzzy connected image segmentation: theory, algorithms, and validation. Comput Vis Image Underst 77:145–174CrossRef

Saint-Marc P, Chen JS, Medioni G (1991) Adaptive smoothing: a general tool for early vision. IEEE Trans Pattern Anal Mach Intell 6:514–529CrossRef

Tomasi C, Manduchi, R (1998). Bilateral filtering for gray and color images. In: IEEE international conference computer vision (ICCV 1998), pp 839–846

Weickert J (1998) Anisotropic diffusion in image processing. Teubner, StuttgartMATH

Weiss B (2006) Fast median and bilateral filtering. ACM Trans Graphics (TOG) 25(3):519–526CrossRef

Zhang J (1992) The mean field theory in EM procedures for Markov random fields. IEEE Trans Signal Process 40(10):2570–2583CrossRefMATH

Title: Image Enhancement
Author: Klaus D. Toennies
Publisher: Springer London
Book: Guide to Medical Image Analysis
Print ISBN: 978-1-4471-7318-2

Electronic ISBN: 978-1-4471-7320-5

Copyright Year: 2017
DOI: https://doi.org/10.1007/978-1-4471-7320-5_4

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