Application of an improved version of JPEG2000 based on mathematical morphology to medical images

Bennacer, Layachi; Bouledjfane, Badreddine; Ali, Amine Nait

doi:10.1109/setit.2012.6481952

Cited by 3 publications

(1 citation statement)

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“…Mathematical morphology is extensively used in various areas, such as computer vision and machine learning [1], texture and image analysis [2,3], color image processing [4], remote sensing image analysis [5], image compression [6], and video segmentation [7]. Morphological computing has commonly been implemented using processors such as CPU or DSP.…”

Section: Introductionmentioning

confidence: 99%

Reconfigurable Morphological Processor for Grayscale Image Processing

Zhang

2021

Electronics

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Grayscale morphology is a powerful tool in image, video, and visual applications. A reconfigurable processor is proposed for grayscale image morphological processing. The architecture of the processor is a combination of a reconfigurable grayscale processing module (RGPM) and peripheral circuits. The RGPM, which consists of four grayscale computing units, conducts grayscale morphological operations and implements related algorithms of more than 100 f/s for a 1024 × 1024 image. The periphery circuits control the entire image processing and dynamic reconfiguration process. Synthesis results show that the proposed processor can provide 43.12 GOPS and achieve 8.87 GOPS/mm2 at a 220-MHz system clock. The simulation and experimental results show that the processor is suitable for high-performance embedded systems.

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