Image analysis and partitioning for FPGA implementation of image restoration

Ogrenci, S.; Bazargan, Kaveh; Sarrafzadeh, Majid

doi:10.1109/sips.2000.886733

2000 IEEE Workshop on SiGNAL PROCESSING SYSTEMS. SiPS 2000. Design and Implementation (Cat. No.00TH8528)

DOI: 10.1109/sips.2000.886733

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Image analysis and partitioning for FPGA implementation of image restoration

S. Ogrenci

Kaveh Bazargan²,

Majid Sarrafzadeh³

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“…A several techniques have appeared in the literature to provide solutions to the restoration problem see, for example, Analysis and FPGA Implementation of Image Restoration under Resource Constraints is presented in [2]. Image Analysis and Partitioning for FPGA Mapping is presented in [3]. Issues in real-time image processing on a custom-computing platform are discussed in [4].…”

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Design of an Iterative Image Restoration Algorithm Using Fpga

Hassan¹,

Ismail²,

Hamza³

2006

The International Conference on Electrical Engineering

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Programmable logic is emerging as an attractive solution for many digital signal processing application. This paper presents an FPGA implementation of an iterative image restoration technique. The simulation results show the speedup that can be achieved by implementing this algorithm on reconfigurable hardware as compared to the implementation of the algorithm using software. The process from design entry to files download are introduced.

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Design of an Iterative Image Restoration Algorithm Using Fpga

Hassan¹,

Ismail²,

Hamza³

2006

The International Conference on Electrical Engineering

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Feature Identification of Hepatic Cancer Ultrasound Image using Gaussian Filtering Combined with Intensity Adjustment

Fahnun¹,

Mutiara²,

Harlan³

et al. 2019

IJERT

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Image analysis and partitioning for FPGA implementation of image restoration

Cited by 2 publications

References 6 publications

Design of an Iterative Image Restoration Algorithm Using Fpga

Design of an Iterative Image Restoration Algorithm Using Fpga

Feature Identification of Hepatic Cancer Ultrasound Image using Gaussian Filtering Combined with Intensity Adjustment

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