Image Analogy Based Document Image Compression

In this work, we propose an image analogy based super-resolution technique that can be used as an effective tool for document image compression and multi-resolution viewing of the document. The technique uses Dugad and Ahuja method for resizing document images. Next, image analogies framework is applied to add the missing high frequency information. The encoder allows user to compress spatially lower resolution version of the image using any standard image compression technique, thus enabling substantial compression. At the decoder end, the image is resized using Dugad and Ahuja method and then enhanced using image analogy by appending the missing high frequency details, using a training pair of the same class of document image.