Stripe Noise Reduction in MODIS Data by Combining Histogram Matching With Facet Filter

The Moderate Resolution Imaging Spectrometer (MODIS) aboard Terra and Aqua platforms are contaminated by stripe noises. There are three types of stripe noises in MODIS data: detector-to-detector stripes, mirror side stripes, and noisy stripes. Without correction, stripe noises will cause processing errors to the other MODIS products. In this paper, a noise-reduction algorithm is developed to reduce the stripe noise effects in both Terra MODIS and Aqua MODIS data by combining a histogram-matching algorithm with an iterated weighted least-squares (WLS) facet filter. Histogram matching corrects for detector-to-detector stripes and mirror side stripes. The iterated WLS facet filter corrects for noisy stripes. The method was tested on heavily striped Terra MODIS and Aqua MODIS images. Results of Terra MODIS and Aqua MODIS data show that the proposed algorithm reduced stripes noises without degrading image quality. To evaluate performance of the proposed method, quantitative and qualitative analyses were carried out by visual inspection and quality indexes of destriped images