A FPGA Implementation of Variable Kernel Convolution

Šťava, Martin; Tvrdík, Pavel

doi:10.1109/pdcat.2007.45

Cited by 8 publications

(2 citation statements)

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“…These filters are efficient to implement and can be generally used by engineers in practical vision applications [6]. …”

Section: Figure2 Image With 30% Salt and Pepper Noisementioning

confidence: 99%

“…On the other hand computer vision is often considered highlevel image processing out of which a machine/computer/software intends to decipher the physical contents of an image or a sequence of images (e.g., videos or 3D full-body magnetic resonance scans) [5].In this paper we take an example of convolution using FPGA was developed using [3*3] sobel filter using a [15*15] image. [6].…”

Section: Introductionmentioning

confidence: 99%

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Reducing the Computation Complexity of 2-D Gaussian Filter

raj

Singal²,

kumari³

2017

ijsrm

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Abstract-Now a day's we are facing a problem regarding smoothing of the image.One of the very useful method to smoothing the image is 2-D Gaussian Filter, which is used in Image Processing. However, the heavy computational resources are required by 2-D Gaussian Filter, and it comes down to real-time applications. The vital efficiency is achieved in this implementation. We use floating-point representation, but there are certain obstacle for this implementation because it requires large computational power in order to achieve real-time image processing. On the other hand a fixed-point approach is much more suitable for the implementation of a 2-D Gaussian filter in FPGA.By using fixed-point arithmetic for the implementation, the efficiency is increases, size of area decreases, complexity decreases and the computational cost is also reduced.In this paper we reduced the LUT by 11.34 % by using Gaussian filter.

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“…These filters are efficient to implement and can be generally used by engineers in practical vision applications [6]. …”

Section: Figure2 Image With 30% Salt and Pepper Noisementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%