Cluster based block processing for gigantic images: Dimension and size

Processing gigantic images with normal image processing techniques can be time consuming and difficult. Here gigantic mean with respect to dimension (Giga Pixels) or memory size (Giga Bytes). These images can be sometimes too large to load into the memory or they can be loaded, but then takes more time for processing. To overcome this problem, we proposed a method, Cluster Based Block Processing, to process large images by splitting the image according to their dimension or size and process it on different machine in the Hadoop cluster using Map-Reduce for effective processing. Representative results of comprehensive experiments on gigantic images are selected to validate the capacity of our proposed method over the traditional methods. Our results show that the proposed method is 20× faster than existing traditional methods.