A Modified Kernels-Alternated Error Diffusion Watermarking Algorithm for Halftone Images
IWDW '07 Proceedings of the 6th International Workshop on Digital Watermarking
IWDW '07 Proceedings of the 6th International Workshop on Digital Watermarking
Self Embedding Watermarking Scheme Using Halftone Image
IEICE - Transactions on Information and Systems
Transactions on Data Hiding and Multimedia Security IV
IEEE Transactions on Image Processing
Analysis of green noise error diffusion
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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Digital halftoning quantizes a graylevel image to one bit per pixel. Halftoning by error diffusion reduces local quantization error by filtering the quantization error in a feedback loop. In this paper, we linearize error diffusion algorithms by modeling the quantizer as a linear gain plus additive noise. We confirm the accuracy of the linear model in three independent ways. Using the linear model, we quantify the two primary effects of error diffusion: edge sharpening and noise shaping. For each effect, we develop an objective measure of its impact on the subjective quality of the halftone. Edge sharpening is proportional to the linear gain, and we give a formula to estimate the gain from a given error filter. In quantifying the noise, we modify the input image to compensate for the sharpening distortion and apply a perceptually weighted signal-to-noise ratio to the residual of the halftone and modified input image. We compute the correlation between the residual and the original image to show when the residual can be considered signal independent. We also compute a tonality measure similar to total harmonic distortion. We use the proposed measures for edge sharpening, noise shaping, and tonality to evaluate the quality of error diffusion algorithms