Computationally Efficient Two Stage Sequential Framework for Stereo Matching
B. N.S, and H.S.Sheshadri. International Journal on Foundations of Computer Science & Technology (IJFCST), 06 (6):
10(September 2022)
Abstract
Almost all the existing stereo algorithms fall under a common assumption that corresponding color or
intensity values will be similar like one another. On the other hand, it is also not that true in practice
where the image color or intensity values are regularly affected by different radiometric factors like
illumination direction, change in image device, illuminant color and so on. For this issue, the information
about the raw color of the images which is recorded by the camera should not depend on it totally, and
also the common assumptions on color consistency doesn’t influence good (great) between the stereo
images in real scenario. Therefore, most of the conventional stereo algorithms can be seriously degraded
in terms of performance under radiometric variations. In this work, we intend to develop a new stereo
matching algorithm which will be insensitive to change in radiometric conditions between stereo pairs i.e.
left image as well as right image. Unlike the other stereo algorithms, we propose a computationally
efficient two stage sequential framework for stereo matching which can handle the various radiometric
variations between the stereo pairs.Experimental results proves that the proposed method outperforms
extremely well compare to other state of the art stereo methods under change in various radiometric
conditions for a given stereo pair and it is also found from the results that the execution time is less
compare to existing methods.
%0 Journal Article
%1 noauthororeditor
%A N.S, Bindu
%A H.S.Sheshadri,
%D 2022
%J International Journal on Foundations of Computer Science & Technology (IJFCST)
%K Stereo bilateral filter matching radiometric rank transform variation
%N 6
%P 10
%T Computationally Efficient Two Stage Sequential Framework for Stereo Matching
%U https://wireilla.com/papers/ijfcst/V6N5/6516ijfcst01.pdf
%V 06
%X Almost all the existing stereo algorithms fall under a common assumption that corresponding color or
intensity values will be similar like one another. On the other hand, it is also not that true in practice
where the image color or intensity values are regularly affected by different radiometric factors like
illumination direction, change in image device, illuminant color and so on. For this issue, the information
about the raw color of the images which is recorded by the camera should not depend on it totally, and
also the common assumptions on color consistency doesn’t influence good (great) between the stereo
images in real scenario. Therefore, most of the conventional stereo algorithms can be seriously degraded
in terms of performance under radiometric variations. In this work, we intend to develop a new stereo
matching algorithm which will be insensitive to change in radiometric conditions between stereo pairs i.e.
left image as well as right image. Unlike the other stereo algorithms, we propose a computationally
efficient two stage sequential framework for stereo matching which can handle the various radiometric
variations between the stereo pairs.Experimental results proves that the proposed method outperforms
extremely well compare to other state of the art stereo methods under change in various radiometric
conditions for a given stereo pair and it is also found from the results that the execution time is less
compare to existing methods.
@article{noauthororeditor,
abstract = {Almost all the existing stereo algorithms fall under a common assumption that corresponding color or
intensity values will be similar like one another. On the other hand, it is also not that true in practice
where the image color or intensity values are regularly affected by different radiometric factors like
illumination direction, change in image device, illuminant color and so on. For this issue, the information
about the raw color of the images which is recorded by the camera should not depend on it totally, and
also the common assumptions on color consistency doesn’t influence good (great) between the stereo
images in real scenario. Therefore, most of the conventional stereo algorithms can be seriously degraded
in terms of performance under radiometric variations. In this work, we intend to develop a new stereo
matching algorithm which will be insensitive to change in radiometric conditions between stereo pairs i.e.
left image as well as right image. Unlike the other stereo algorithms, we propose a computationally
efficient two stage sequential framework for stereo matching which can handle the various radiometric
variations between the stereo pairs.Experimental results proves that the proposed method outperforms
extremely well compare to other state of the art stereo methods under change in various radiometric
conditions for a given stereo pair and it is also found from the results that the execution time is less
compare to existing methods. },
added-at = {2022-12-15T14:33:51.000+0100},
author = {N.S, Bindu and H.S.Sheshadri},
biburl = {https://www.bibsonomy.org/bibtex/2314841a1dfe2749cc3a792969a882b01/devino},
interhash = {7edbb0081de9b9389d065b9b6539c4f0},
intrahash = {314841a1dfe2749cc3a792969a882b01},
journal = {International Journal on Foundations of Computer Science & Technology (IJFCST)},
keywords = {Stereo bilateral filter matching radiometric rank transform variation},
month = sep,
number = 6,
pages = 10,
timestamp = {2022-12-15T14:33:51.000+0100},
title = {Computationally Efficient Two Stage Sequential Framework for Stereo Matching},
url = {https://wireilla.com/papers/ijfcst/V6N5/6516ijfcst01.pdf},
volume = 06,
year = 2022
}