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Published in:

Volume 2 Issue 5
May-2015
eISSN: 2349-5162

Unique Identifier

JETIR1505040

Page Number

1449-1453

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Title

A NOVEL APPROCH FOR IMAGE STABILIZATION AND COMPRESSION MECHANISM USING NEURAL NETWORK

ISSN

2349-5162

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"A NOVEL APPROCH FOR IMAGE STABILIZATION AND COMPRESSION MECHANISM USING NEURAL NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.2, Issue 5, page no.1449-1453, May-2015, Available :http://www.jetir.org/papers/JETIR1505040.pdf

Abstract

Abstract: Image stabilization has become a subject of significant interest and an active research field over the past years due to the wide use of digital imaging devices. The image stabilization process aims at removing irregular motion phenomena from image sequences in order to accomplish a compensated sequence that displays smooth camera movements. A variety of image processing applications requires motion-compensated image sequences as inputs. The unwanted positional vacillations of the video sequence will affect the visual quality and impede the subsequent processes for several applications. An innovative technique for digital image stabilization (DIS) based on the DCT Algorithm is studied. It exploits the basic features of the DCT in order to separate the local motion signal obtained from an image sequence into two different motion vectors. A variety of embedded systems equipped with a digital image sensor, such as handheld cameras, mobile phones, and robots, can produce image sequences with an observed motion caused by two different types of movements: the smooth camera motion (intentional) and the unwanted shaking motion (jitter). Image compression is a problem of reducing the amount of data required to represent a digital image. It is a process intended to yield a compact representation of an image, thereby reducing the image storage/transmission requirements. We present a neural network based Growing Self Organizing Map technique that may be a reliable and efficient way to achieve vector quantization. To verify the effectiveness of the proposed GSOM method, several simulations were performed, and the results were compared with existing stabilization methods. An attempt has been made for estimate Mean square error (MSE), peak signal to noise ratio (PSNR) and structural similarity index (SSIM) to study the performance of GSOM and compared with other existing techniques and showed that HHT-DIS outperforms the existing methods.

Key Words

Keywords: Image Stabilization, Neural Network, GSOM

Cite This Article

"A NOVEL APPROCH FOR IMAGE STABILIZATION AND COMPRESSION MECHANISM USING NEURAL NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.2, Issue 5, page no. pp1449-1453, May-2015, Available at : http://www.jetir.org/papers/JETIR1505040.pdf

Publication Details

Published Paper ID: JETIR1505040
Registration ID: 150476
Published In: Volume 2 | Issue 5 | Year May-2015
DOI (Digital Object Identifier):
Page No: 1449-1453
ISSN Number: 2349-5162

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Cite This Article

"A NOVEL APPROCH FOR IMAGE STABILIZATION AND COMPRESSION MECHANISM USING NEURAL NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.2, Issue 5, page no. pp1449-1453, May-2015, Available at : http://www.jetir.org/papers/JETIR1505040.pdf




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