Destriping Ocean Color Monitor-2 data
02 May 2016-Vol. 9881, pp 988123
TL;DR: In this article, a pixel-by-pixel approach was proposed to remove the striping effects in the TOA radiance products, which showed significant improvement in image quality for Level 1B radiance and Level 2 (Water leaving radiance (L w ) and biogeochemical) products.
Abstract: Ocean Color Monitor-2 (OCM-2) on-board Oceansat 2 satellite is a multi-spectral sensor with a spatial resolution of 360×250 m . Despite the presence of improved spatial resolution for better ocean color interpretation within coastal zones; differences among the OCM-2 detectors lead to striping artifacts in the along-track direction limiting the ocean color observations. Existing calibration methods do not characterize the striping noise efficiently. Destriping algorithms are generally applied to Level 2 radiance or biogeochemical products ( i.e. , post-radiometric and atmospheric correction), to remove the striping artifacts in order to ensure quality products. The present study focuses to reveal a robust method which effectively removes the striping effects in the TOA radiance products. Preliminary results obtained from this approach have been highlighted which show significant improvement in image quality for Level 1B (TOA radiance) and Level 2 (Water leaving radiance ( L w ) and biogeochemical) products. The proposed method operates on a pixel by pixel basis with an aim to maintain the spatial and spectral resolution of data and ensure image quality in the derived products.
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TL;DR: In this paper, a multiple scattering algorithm for atmospheric correction of satellite ocean colour observations is described, precisely designed for the MERIS instrument, globally assesses the combined contributions of aerosols and molecules to the multiple scattering regime.
Abstract: A multiple scattering algorithm for atmospheric correction of satellite ocean colour observations is described. This algorithm, precisely designed for the MERIS instrument, globally assesses the combined contributions of aerosols and molecules to the multiple scattering regime. The approach was introduced in a previous work, where it was shown that, for a given aerosol, multiple scattering effects can be assessed through the relationship between the aerosol optical thickness and the relative increase in the path radiance that results from the progressive introduction of this aerosol within an aerosol-free atmosphere. Based on considerations about the accuracy to which the water-leaving radiances should be retrieved, the need to account for multiple scattering is argued. The principle of the algorithm is then presented, and tests and sensitivity studies (especially as regards aerosol type and vertical distribution) are performed to assess its performance in terms of errors on the retrieved water-leaving re...
239 citations
TL;DR: An alternative algorithm is suggested which matches the gain and offset of each sensor to typical values, and which is resistant to the effects of outliers.
Abstract: Image destriping is necessary due to sensor-to-sensor variation within instruments. This has most often been done by assuming that each sensor views a statistically similar subimage, and a histogram of each sensor's response is made to match the overall histogram. Histogram matching shows sensitivity to violations of the similarity assumption. An alternative algorithm is suggested which matches the gain and offset of each sensor to typical values, and which is resistant to the effects of outliers. Tests on a sample image show the moment matching algorithm reduces the variance between sensors to a greater degree than histogram matching.
231 citations
TL;DR: Methods are presented for obtaining the required information directly from the statistics of the sensor outputs for destriping of LANDSAT Multispectral Scanner images, applying to images obtained with any multisensor line-scan camera.
222 citations
TL;DR: Basic statistical assumptions used in previous techniques are replaced by a much realistic geometrical consideration on the striping unidirectional variations and the resulting algorithm is tested on Aqua and Terra MODIS data contaminated with severe stripes and is shown to provide optimal qualitative and quantitative results.
Abstract: Images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua exhibit strong detector striping. This artifact is common to most pushbroom scanners and affects both visual interpretation and radiometric integrity of remotely sensed data. A considerable effort has been made to remove stripe noise and reduce its impact on high-level products. Despite the variety of destriping algorithms proposed in the literature, complete removal of stripes without signal distortion is yet to be overcome. In this paper, we tackle the striping issue from a variational angle. Basic statistical assumptions used in previous techniques are replaced by a much realistic geometrical consideration on the striping unidirectional variations. The resulting algorithm is tested on Aqua and Terra MODIS data contaminated with severe stripes and is shown to provide optimal qualitative and quantitative results.
180 citations
TL;DR: In this article, the authors investigated the effect of sensor stripes in multisensor imagery and found that they can cause subsequent image classification to fail, if not removed properly, by removing the stripes.
Abstract: Sensor stripes evident in multisensor imagery can cause subsequent image classification to fail, if not removed properly. Of the destriping algorithms investigated, the one published by Horn and Wo...
139 citations