JPEG-MATCHED DATA FILLING OF SPARSE IMAGES (MA-P7)

Author(s) : George Pavlidis (Democritus University of Thrace, Greece) Sofia Tsekeridou (Democritus University of Thrace, Greece) Christodoulos Chamzas (Democritus University of Thrace, Greece)

Abstract : To efficiently compress rasterized compound documents, an encoder must be content-adaptive. Content adaptivity may be achieved by using a layered approach. In such an approach, a compound image is segmented into layers and then, the appropriate encoders are employed to compress these layers individually. A major factor in using these standard encoders efficiently is to match the layers’ characteristics to these of the encoder by using data filling techniques to fill-in the initially sparse layers. In this work we propose a sub-optimal “non-linear projections” scheme that efficiently matches the baseline JPEG coder in compressing background layers, leading to smaller files with better image quality.

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