Mixed Pixels: A Challenge in Remote Sensing Data Classification for Improving Performance
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2012, Vol 1, Issue 9
Abstract
Remote Sensing (RS) refers to the science of identification of earth surface features and estimation of their geo-biophysical properties using electromagnetic radiation as a medium of interaction. Spectral, spatial, temporal and polarization signatures are major characteristics of the sensor/target, which facilitate target discrimination. Earth surface data as seen by the sensors in different wavelengths (reflected, scattered and/or emitted), is radio-metrically and geo-metrically corrected before extraction of spectral information. RS data, with its ability for a synoptic view repetitive coverage with calibrated sensors to detect changes, observations at different resolutions, provides a better alternative for natural resources management as compared to traditional methods. The traditional classification methods have been developed using the image statistics, but their applicability to the processing of data is limited due to the presence of mixed pixels which affect the use of remotely sensed data in Land-Use and Land-Cover (LU/LC) classification and change detection. Various techniques are being used to attempt to ‘unmix’ the information and identify mixing proportions from the pixels and have lead to sub-pixel classification. The purpose of this paper is to understand mixed pixel problems, its significance and techniques developed to ‘unmix’ the pixels, and also to study the various soft classification methods. It is understood that mixed pixel classification could be solved efficiently by Soft Classification methods, and Contextual Classification adopting relaxation labeling would give better results both in Neural Network based and Fuzzy Logic based Classification. Some of the major operational application themes, in which India has extensively used remote sensing data, are agriculture, forestry, water resources, land use, urban sprawl, geology, environment, coastal zone, marine resources, snow and glacier, disaster monitoring and mitigation, infrastructure development, etc.
Authors and Affiliations
A. L. Choodarathnakara, , Dr. T. Ashok Kumar, , Dr. Shivaprakash Koliwad, , Dr. C. G. Patil,
Keywords
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