An adaptive high-throughput edge detection filtering system using dynamic partial reconfiguration

Orlandić, Milica; Svarstad, Kjetil

doi:10.1007/s11554-018-0753-4

Cited by 8 publications

(2 citation statements)

References 20 publications

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“…The parallel architecture makes the calculation of processors more efficient. In addition, a parallel and pipelined architecture based implementation method was proposed in [23] to implement the edge detection algorithm. Although the manual implementation method needs complex programming and a long development cycle, the designs based on the manual implementation method above have the characteristics of high throughput and computing performance.…”

Section: Background a Related Workmentioning

confidence: 99%

FPGA-Based Implementation of Ship Detection for Satellite On-Board Processing

Chen

Shi

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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At present, the raw echo data captured by spaceborne SAR is usually downlinked to the ground stations for imaging and analysis. If the SAR data can be processed on-board, the processing results could be transmitted to users directly through broadcast distribution, which can greatly reduce the delay time for emergency applications. However, on-board processing implementation faces many challenges due to the space radiation environment and limited resources of the satellite. In this paper, an FPGA-based implementation of ship detection for on-board processing is proposed, which has high efficiency in logic and memory resources. First, the hardware-oriented clustering approach is proposed. Image processing operations with similar regularity of data access can be mapped in one processing engine, which can reduce the employment of logic resources. Second, the concept of the data-buffering cycle (DBC) is proposed. The DBC provides a method to analyze the intermediate data and optimize the memory reuse. Finally, based on the above optimization methods, the FPGA-based implementation for a ship detection algorithm is presented. Compared with the traditional methods, the experimental results show the efficacy of our proposed method with lower consumption in logic and memory resources.

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Section: Background a Related Workmentioning

confidence: 99%

FPGA-Based Implementation of Ship Detection for Satellite On-Board Processing

Chen

Shi

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…Such edge detectors or operators are relatively sensitive to noise and often enhance noise while detecting edges. The morphological edge detector mainly uses the concept of morphological gradient, although it is also sensitive to noise but does not enhance or amplify the noise [27,28].…”

Section: Introductionmentioning

confidence: 99%

Image Edge Recognition of Virtual Reality Scene Based on Multi-Operator Dynamic Weight Detection

Liu

Chen

et al. 2020

IEEE Access

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Image edge detection in virtual reality scenes is one of the most important technologies in the field of image processing and computer vision. It occupies an important position in the image processing system and is a key factor that affects the performance of the entire system. The quality of the algorithm directly affects the performance of the computer's visual system. This paper briefly describes the basic theoretical methods of image edge detection. The basic theory and processing flow of image edge detection are analyzed, and several commonly used edge detection preprocessing methods and their basic principles are elaborated in detail. The existing traditional edge detection methods are briefly introduced, and the traditional edge detection methods are compared. This paper studies the adaptive multi-scale edge detection method based on Canny algorithm, and through theoretical analysis, compares the advantages and disadvantages of various algorithms in image edge detection. In the process of acquiring image edges, the local maximum value of the modulus is calculated along the gradient direction and the threshold is adaptively selected based on the image blocking principle. Comparing with the traditional modulus maximum edge detection method, this algorithm overcomes the contradiction that can suppress the interference of noise and obtain better edge detection effect to a certain extent. Experiments show that the method in this paper not only suppresses the interference of impulsive noise to the image edge detection, but also greatly reduces the possibility of false edges, and obtains a satisfactory accurate binary edge image. INDEX TERMS edge detection; multiple operators; adaptive dynamic weights; virtual reality scenes.

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A study on VLSI implementation of image enhancement techniques

Aklak

Pugazhenthi²,

Alex

2021

Concurrency and Computation

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In real-time, the images captured are not always appreciable for visual perception.The quality of the image relies on the illumination condition. Contrast enhancement is required to improve the visual quality of the image. In this article, the image enhancement techniques that are adaptable for real-time images are studied. Further, an investigation is done on implementing the image processing algorithms in very large-scale integration (VLSI) hardware. As the image data are comparatively larger, the computational complexity and the memory requirement are more. From the study, the need for efficient computation of such image processing algorithms is realized. The efficient computation of image processing algorithms on hardware platforms, in particular on field programmable gate array (FPGA), is reviewed. As an experiment, the gamma-transformation technique used for image enhancement is realized. Initially, the prototype is modeled using MATLAB, and then it is implemented using an FPGA. K E Y W O R D Sfield programmable gate array, floating point multiplier, image enhancement INTRODUCTIONIn the modern digital world, all multimedia transactions require good-quality images. The visibility of an image depends on the illuminance and reflectance of the scene in the real world. The brightness of a point in an image is non-linear to the brightness of the same point in the real world.Generally, lighting condition determines the quality of an image. The images taken under poor lighting conditions may cause discomfort while viewing images.The image acquired can be degraded due to various reasons such as sensor level malfunction, low visibility, excessive exposure, foggy conditions, and so on. 1 To overcome the degradation, pre-processing is required to enhance the image. Image enhancement is the process of adjusting digital images so that the results are more suitable for display or further processing. It includes processes like deblurring, noise removal, filtering, and so on.Not all images will require the same image enhancement technique because there may be over-exposed regions in outdoor images that will need different treatment compared to indoor images. In literature, there are many algorithms proposed for image enhancement. The technique of being applied for enhancement depends on the input quality of the image. The quality needs to be assessed before applying any approach for a better perception of the image. A real-time implementation of image enhancement is hard to design using software because a large data set is required to represent an image. Since field programmable gate arrays (FPGAs) could exploit the spatial parallelism in image enhancement algorithms they are widely used for hardware implementation.Realizing the design on FPGAs, offer a compromise between the flexibility of general-purpose processors and the hardware-based speed of an integrated-circuit design. 2 Also, the programmable property of FPGA makes them a good choice for image processing applications, as the processing of the number of images also...

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An adaptive high-throughput edge detection filtering system using dynamic partial reconfiguration

Cited by 8 publications

References 20 publications

FPGA-Based Implementation of Ship Detection for Satellite On-Board Processing

FPGA-Based Implementation of Ship Detection for Satellite On-Board Processing

Image Edge Recognition of Virtual Reality Scene Based on Multi-Operator Dynamic Weight Detection

A study on VLSI implementation of image enhancement techniques

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