Abstract
A parallel block processing for remote sensed images for classification problem is presented in this paper. Due to increase in computational time for processing the remote sensing images for pixel dimension more than 1000 × 1000. Block processing approach is applied for an image in parallel by distributing the task among the cores. K -means is one of the widely used clustering method for analyzing features in images. Hence it is considered for the parallel block processing approach. The parallel Block Processing approach was implemented using Matlab 2014a programming environment. The experiment is carried out on data sets comprising of 200 samples of high resolution orthoimagery satellite images. The result obtained from parallel block processing approach lead to efficient usage of hardware resources, depletion in time compared to sequential K -means algorithm. Results are acceptable and this approach can be applied for image processing operations.
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