DocumentCode :
1430519
Title :
Quantization error in regular grids: triangular pixels
Author :
Kamgar-Parsi, B. ; Kamgar-Parsi, B.
Author_Institution :
Navy Centre for Appl. Res. in Artificial Intelligence, Naval Res. Lab., Washington, DC, USA
Volume :
7
Issue :
10
fYear :
1998
fDate :
10/1/1998 12:00:00 AM
Firstpage :
1496
Lastpage :
1500
Abstract :
Quantization of the image plane into pixels results in the loss of the true location of features within pixels and introduces an error in any quantity computed from feature positions in the image. We derive closed-form, analytic expressions for the error distribution function, the mean absolute error (MAE), and the mean square error (MSE) due to triangular tessellation, for differentiable functions of an arbitrary number of independently quantized points, using a linear approximation of the function. These quantities are essential in examining the intrinsic sensitivity of image processing algorithms. Square and hexagonal pixels were treated in previous papers. An interesting result is that for all possible cases 0.99<D¯T/D¯S<1.13, where D¯T and D¯S are the MAE in triangular and square tessellations
Keywords :
approximation theory; error analysis; feature extraction; image sampling; quantisation (signal); closed-form analytic expressions; differentiable functions; error distribution function; image feature positions; image plane; image processing algorithms; linear approximation; mean absolute error; mean square error; quantization error; regular grids; square sampling; square tessellation; triangular pixels; triangular sampling; triangular tessellation; Circuits; Decoding; Image coding; Image processing; Image reconstruction; Least squares methods; Pixel; Quantization; Testing; Video compression;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/83.718490
Filename :
718490
Link To Document :
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