DCT-based algorithm to remove vertical stripings from Ocean Colour Monitor (OCM) data in Indian Remote Sensing Satellite (IRS-P4)

Santosh Kumar Tripathi; Nitant Dube; R. Ramakrishnan

doi:10.1117/12.693950

22 December 2006 DCT-based algorithm to remove vertical stripings from Ocean Colour Monitor (OCM) data in Indian Remote Sensing Satellite (IRS-P4)

Santosh Kumar Tripathi, Nitant Dube, R. Ramakrishnan

Author Affiliations +

Proceedings Volume 6405, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications; 64052D (2006) https://doi.org/10.1117/12.693950
Event: SPIE Asia-Pacific Remote Sensing, 2006, Goa, India

Abstract

IRS-P4(Oceansat-1) is the first in the series of Indian operational ocean remote sensing satellites. The payloads of this mission are tailored for making measurements of the physical and biological oceanographic parameters. IRS-P4 contains two sensors, namely Ocean Colour Monitor (OCM) and MSMR. OCM has 8-bands, in which first band, intermittently shows vertical stripings in the raw data. An algorithm based on Discrete Cosine Transform(DCT), is proposed here to model these vertical stripings. Some of the basis function of the DCT has very high degree of similarity with the vertical strips. This work elliminates the vertical strips present in the image by modelling the appropriate coefficients of the basis functions. Results of our work shows that the approach followed by us is effective in removing the vertical strips. To avoid the computational overheads of application of this algorithm on large image, we have divided the image into smaller blocks, the issues of block based processing in frequency domain has been taken care by handling the boundary conditions by means of smoothening.

Citation Download Citation

Santosh Kumar Tripathi, Nitant Dube, and R. Ramakrishnan "DCT-based algorithm to remove vertical stripings from Ocean Colour Monitor (OCM) data in Indian Remote Sensing Satellite (IRS-P4)", Proc. SPIE 6405, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications, 64052D (22 December 2006); https://doi.org/10.1117/12.693950

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KEYWORDS

Image processing

Image quality

Error analysis

Clouds

Remote sensing

Satellites

Signal to noise ratio

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