In *Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on*, volume 2, pages 59 -63 vol.2, oct, 1998.

doi abstract bibtex

doi abstract bibtex

We present an inverse halftoning algorithm for error diffused halftones. At each pixel, the algorithm applies a separable 7 times;7 FIR filter parameterized by the computed local horizontal and vertical gradients. All operations are entirely local; only 7 rows of image storage and fewer than 300 operations per pixel are required. The algorithm can be easily implemented in embedded software or hardware. We compare our algorithm with previously reported approaches, and show that it delivers comparable PSNR and subjective quality at a fraction of the computation and memory requirements. A C implementation of the algorithm is available

@inproceedings{723317, Author = {Kite, T.D. and Damera-Venkata, N. and Evans, B.L. and Bovik, A.C.}, Booktitle = {Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on}, Date-Added = {2012-10-22 15:14:10 +0000}, Date-Modified = {2012-10-22 15:14:10 +0000}, Doi = {10.1109/ICIP.1998.723317}, Keywords = {C implementation;PSNR;error diffused halftones;high quality fast inverse halftoning algorithm;horizontal gradient;image storage;operations;separable 7 times;7 FIR filter;subjective quality;vertical gradient;C language;FIR filters;adaptive filters;image processing;low-pass filters;}, Month = {oct}, Pages = {59 -63 vol.2}, Title = {A high quality, fast inverse halftoning algorithm for error diffused halftones}, Volume = {2}, Year = {1998}, Abstract = {We present an inverse halftoning algorithm for error diffused halftones. At each pixel, the algorithm applies a separable 7 times;7 FIR filter parameterized by the computed local horizontal and vertical gradients. All operations are entirely local; only 7 rows of image storage and fewer than 300 operations per pixel are required. The algorithm can be easily implemented in embedded software or hardware. We compare our algorithm with previously reported approaches, and show that it delivers comparable PSNR and subjective quality at a fraction of the computation and memory requirements. A C implementation of the algorithm is available}, Bdsk-Url-1 = {http://dx.doi.org/10.1109/ICIP.1998.723317}}

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