Enhancement of Coupled Multichannel Images Using Sparsity Constraints

• Published in: IEEE transactions on image processing Vol. 19; no. 8; pp. 2115 - 2126
• Main Authors: Ramakrishnan, Naveen, Ertin, Emre, Moses, Randolph L
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2010; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Biological and medical sciences; Biomedical imaging; Color; Computerized, statistical medical data processing and models in biomedicine; Constraint optimization; Deconvolution; Detection, estimation, filtering, equalization, prediction; Equivalence; Exact sciences and technology; Frequency; Hyperspectral imaging; Image enhancement; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image processing; Information, signal and communications theory; Interferometric synthetic aperture radar; Interferometric synthetic aperture radar (IFSAR); Layout; Magnetic resonance imaging; Mathematical models; medical imaging; Medical management aid. Diagnosis aid; Medical sciences; Multichannel; multichannel images; nonquadratic regularization; Numerical Analysis, Computer-Assisted; Optimization; Pattern Recognition, Automated - methods; Reproducibility of Results; Sensitivity and Specificity; Signal and communications theory; Signal processing; Signal Processing, Computer-Assisted; Signal resolution; Signal, noise; Subtraction Technique; Synthetic aperture radar; Synthetic aperture radar interferometry; Telecommunications and information theory; Image processing; Joint; Algorithm; Optimization; Complex variable method; Regularization method; Image quality; multichannel images; Descent method; Radar imaging; Medical imagery; nonquadratic regularization; Multiple channel; Image enhancement; Synthetic aperture radar; Interferometric synthetic aperture radar (IFSAR); medical imaging
• ISSN: 1057-7149; 1941-0042; 1941-0042
• DOI: 10.1109/TIP.2010.2045701

We consider the problem of joint enhancement of multichannel images with pixel based constraints on the multichannel data. Previous work by Çetin and Karl introduced nonquadratic regularization methods for SAR image enhancement using sparsity enforcing penalty terms. We formulate an optimization problem that jointly enhances complex-valued multichannel images while preserving the cross-channel information, which we include as constraints tying the multichannel images together. We pose this problem as a joint optimization problem with constraints. We first reformulate it as an equivalent (unconstrained) dual problem and develop a numerically-efficient method for solving it. We develop the Dual Descent method, which has low complexity, for solving the joint optimization problem. The algorithm is applied to both an interferometric synthetic aperture radar (IFSAR) problem, in which the relative phase between two complex-valued images indicate height, and to a synthetic multimodal medical image example.