An Efficient Total Variation Minimization Method for Image Restoration
Cong Thang Pham, Thi Thu Thao Tran, Guilhem Gamard
Abstract
In this paper, we present an effective algorithm for solving the Poisson–Gaussian total variation model. The existence and uniqueness of solution for the mixed Poisson–Gaussian model are proved. Due to the strict convexity of the model, the split-Bregman method is employed to solve the minimization problem. Experimental results show the effectiveness of the proposed method for mixed Poisson–Gaussion noise removal. Comparison with other existing and well-known methods is provided as well.
Topics & Concepts
UniquenessConvexityPoisson distributionMinificationVariation (astronomy)GaussianShot noiseMathematicsMathematical optimizationApplied mathematicsTotal variation denoisingGaussian noiseImage restorationImage (mathematics)Computer scienceAlgorithmImage processingStatisticsArtificial intelligenceMathematical analysisPhysicsAstrophysicsTelecommunicationsFinancial economicsEconomicsDetectorQuantum mechanicsImage and Signal Denoising MethodsAdvanced Image Processing TechniquesSparse and Compressive Sensing Techniques