I-wizard the neural network based image compressor - Cheng, Dennis T. (1999)
There are many reasons why the use of digital images is so popular. For one, they are very clear and can be easily manipulated. The negative side of these is that digital form requires a large number of bits to represent even a single digital image. Furthermore, the total volume of digital images produced each day increases as more applications are found. Situation: An electronic still camera using a single-chip CCD sensor (with a color filter array) might require 484 x 768 pixels x 8 bits/pixel, resulting in about 3x10 to the sixth bits/image. A 1-megabyte solid-state memory card used on-board the camera could store less than three images in uncompressed form. Obviously, this is neither convenient nor cost-effective. If an 8:1 compression ratio (defined as the ratio of the number of bits used for the original image to the number of bits for the compressed image) can be achieved, the memory card can then hold 24 images, making the system competitive in terms of storage with a conventional film-based camera using a 24-exposure roll. As a result, it becomes necessary to find efficient ways for digital images in order to: 1. reduce the memory required for storage 2. improve the data access from storage devices 3. reduce the bandwidth and/or the time required for transfer across communication channels. In this paper, a compression technique that uses a hybrid of lossless and lossy compression schemes was developed. This technique is composed of algorithms which include vector quantization, arithmetic coding and a neural network-based process, self-organizing map (SOM).