title: High-quality MRC document coding.
abstract: The mixed raster content (MRC) model can be used to implement highly effective document compression algorithms. MRC document coders are typically based on the use of a binary mask layer that efficiently encodes the text and graphic content. However, while many MRC-based methods can yield much higher compression ratios than conventional color image compression methods, the binary representation tends to distort fine document details, such as thin lines and text edges. In this paper, we propose a method for encoding and decoding the binary mask layer that substantially improves the decoded document fidelity of text and graphics at a fixed bit rate. This method, which we call resolution-enhanced rendering (RER), works by adaptively dithering the encoded binary mask, and then applying a nonlinear predictor to decode a gray level mask at the same resolution. Both the dithering and nonlinear prediction algorithms are jointly optimized to produce the minimal distortion rendering. In addition, we introduce a second method, interpolative RER (IRER), which incorporates interpolation into the MRC decoder. The IRER method increases the compression ratio by allowing a high-resolution document to be coded at lower resolutions. We present experimental results illustrating the performance of our RER/IRER methods and comparing them to some existing MRC-based compression algorithms.
authors.affiliation: Ricoh Innovations Inc, Menlo Park, CA 94025-7054, USA. feng@rii.ricoh.com
authors.forename: Guotong
authors.initials: G
authors.lastname: Feng
authors.forename: Charles A
authors.initials: CA
authors.lastname: Bouman
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D044962:Data Compression / Q000379:methods*; D004282:Documentation / Q000379:methods*; D001330:Electronic Data Processing / Q000379:methods*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*