Gray-scale erosion algorithm based on image bitwise decomposition: Application to Focal Plane Processors

Frias-Velazquez, Andres; Morros, Josep Ramon

doi:10.1109/icassp.2009.4959716

Cited by 3 publications

(3 citation statements)

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“…and the threshold bitplanes at levels u j,k = (2j + 1)2 k and v j,k = (j + 1)2 k+1 are generated from the set of bitwise bitplanes B = (B 0 , ..., B K−1 ) using (6). Finally, we can express a filtered threshold bitplane as T = Φ s,f [T ] to later rewrite (9) more compactly as follows:…”

Section: The Bitplane Stack Filter Algorithmmentioning

confidence: 99%

“…The algorithm runs from the most to the least significant bitplane because each processing block depends on bitplanes of greater or equal significance than the k-th block. This hierarchization is related to the number of bitwise bitplanes required to generate T u and T v using (6). For instance, to compute T u using bitwise bitplanes, we need the p most significant bitplanes such that p = K − k. On the other hand, to compute T v we need the q most significant bitplanes such that q ≤ K − k − 1.…”

Section: The Proposed Algorithmmentioning

confidence: 99%

“…It is worth to remark that an early development of the method described above was presented in our previous paper [6]. This prototype method also benefits from the bitwise decomposition and the bitplane architecture; however, it was specifically tailored to the erosion filter.…”

Section: Introductionmentioning

confidence: 99%

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Hierarchical stack filtering: a bitplane-based algorithm for massively parallel processors

Frias-Velazquez

Morros

García

et al. 2017

J Real-Time Image Proc

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With the development of novel parallel architectures for image processing, the implementation of well-known image operators needs to be reformulated to take advantage of the so-called massive parallelism. In this work, we propose a general algorithm that implements a large class of nonlinear filters, called stack filters, with a 2D-array processor. The proposed method consists of decomposing an image into bitplanes with the bitwise decomposition and then processes every bitplane hierarchically. The filtered image is reconstructed by simply stacking the filtered bitplanes according to their order of significance. Owing to its hierarchical structure, our algorithm allows us to trade-off between image quality and processing time, and to significantly reduce the computation time of low-entropy images. Also, experimental tests show that the processing time of our method is substantially lower than that of classical methods when using large structuring elements. All these features are of interest to a variety of real-time applications based on morphological operations such as video segmentation and video enhancement.Peer ReviewedPostprint (author's final draft

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Section: The Bitplane Stack Filter Algorithmmentioning

confidence: 99%

Section: The Proposed Algorithmmentioning

confidence: 99%