Abstract:

A novel noisereduction model is proposed to remove the multitype stripe noises by combining moment matching with variationalbased method, based on analyzing the characteristics of three types of stripe noises in moderate resolution imaging spectroradiometer (MODIS) data. Firstly, moment matching method is employed for preprocessing the MODIS imagery. Secondly, the variational method is performed to remove the stripe noises left in the image. The energy functional consists of L1 regularization term, image data fidelity term and image gradient fidelity term. Split Brgman iteration is adopted to achieve the optimization solution of the proposed energy functional. Experimental results indicate that the proposed model can reduce stripes in MODIS data effectively. Compared with destriping approaches including moment matching, lowpass filter and unidirectional variational destriping, the proposed model can preserve the details of the MODIS image and alleviate the block effects caused by regularizationbased methods better.