Abstract
Digital image data compression is a rapidly evolving field with fast growing applications in engineering. Its techniques are motivated from the other fields such as optics, digital signal processing, estimation theory, information theory, stochastic processes, computer graphics, and so on. Often, digital image data compression represents a prerequisite step to develop fast and efficient processing techniques such as filtering, error detection, and reconstruction. This thesis addresses the fundamentals of the major topics of digital image data compression with an approach utilizing a special-modeled source: Differential Pulse Code Modulation (DPCM) with autoregressive sources. It also provides the discussion of the Adaptive Correlated Switching Predictors for DPCM (ACSP-DPCM) which adapt the correlation values per block. ACSP-DPCM will be analyzed, designed, and compared to the median predictor DPCM (PM-DPCM) system.
Kim, Tae Woo (1995). DPCM system with Adaptive Correlated Switching Predictor for image. Master's thesis, Texas A&M University. Available electronically from
https : / /hdl .handle .net /1969 .1 /ETD -TAMU -1995 -THESIS -K563.