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A procedure for high resolution satellite imagery quality assessment.

Crespi M, De Vendictis L - Sensors (Basel) (2009)

Bottom Line: Nevertheless, it is often useful to have tools to evaluate image quality also at the final user level.Image quality is defined by some parameters, such as the radiometric resolution and its accuracy, represented by the noise level, and the geometric resolution and sharpness, described by the Modulation Transfer Function (MTF).This paper proposes a procedure to evaluate these image quality parameters; the procedure was implemented in a suitable software and tested on high resolution imagery acquired by the QuickBird, WorldView-1 and Cartosat-1 satellites.

View Article: PubMed Central - PubMed

Affiliation: DITS, Area di Geodesia e Geomatica - Sapienza Università di Roma - via Eudossiana 18 - 00184 Rome, Italy.

ABSTRACT
Data products generated from High Resolution Satellite Imagery (HRSI) are routinely evaluated during the so-called in-orbit test period, in order to verify if their quality fits the desired features and, if necessary, to obtain the image correction parameters to be used at the ground processing center. Nevertheless, it is often useful to have tools to evaluate image quality also at the final user level. Image quality is defined by some parameters, such as the radiometric resolution and its accuracy, represented by the noise level, and the geometric resolution and sharpness, described by the Modulation Transfer Function (MTF). This paper proposes a procedure to evaluate these image quality parameters; the procedure was implemented in a suitable software and tested on high resolution imagery acquired by the QuickBird, WorldView-1 and Cartosat-1 satellites.

No MeSH data available.


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WV1_RM signal-to-noise ratio (R) level estimation.
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f28-sensors-09-03289: WV1_RM signal-to-noise ratio (R) level estimation.

Mentions: For QuickBird images the whole bit interval (0 – 2,048) was divided in 15 classes, 32 grey levels wide between 256 and 511 bits and 255 grey levels wide, between 0 and 255 bits and between 511 and 2,048 bits (Figure 26 and 27). For WorldView-1 images the whole bit interval (0 – 2,048) was divided as for the QuickBird imagery (Figure 28).


A procedure for high resolution satellite imagery quality assessment.

Crespi M, De Vendictis L - Sensors (Basel) (2009)

WV1_RM signal-to-noise ratio (R) level estimation.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3297129&req=5

f28-sensors-09-03289: WV1_RM signal-to-noise ratio (R) level estimation.
Mentions: For QuickBird images the whole bit interval (0 – 2,048) was divided in 15 classes, 32 grey levels wide between 256 and 511 bits and 255 grey levels wide, between 0 and 255 bits and between 511 and 2,048 bits (Figure 26 and 27). For WorldView-1 images the whole bit interval (0 – 2,048) was divided as for the QuickBird imagery (Figure 28).

Bottom Line: Nevertheless, it is often useful to have tools to evaluate image quality also at the final user level.Image quality is defined by some parameters, such as the radiometric resolution and its accuracy, represented by the noise level, and the geometric resolution and sharpness, described by the Modulation Transfer Function (MTF).This paper proposes a procedure to evaluate these image quality parameters; the procedure was implemented in a suitable software and tested on high resolution imagery acquired by the QuickBird, WorldView-1 and Cartosat-1 satellites.

View Article: PubMed Central - PubMed

Affiliation: DITS, Area di Geodesia e Geomatica - Sapienza Università di Roma - via Eudossiana 18 - 00184 Rome, Italy.

ABSTRACT
Data products generated from High Resolution Satellite Imagery (HRSI) are routinely evaluated during the so-called in-orbit test period, in order to verify if their quality fits the desired features and, if necessary, to obtain the image correction parameters to be used at the ground processing center. Nevertheless, it is often useful to have tools to evaluate image quality also at the final user level. Image quality is defined by some parameters, such as the radiometric resolution and its accuracy, represented by the noise level, and the geometric resolution and sharpness, described by the Modulation Transfer Function (MTF). This paper proposes a procedure to evaluate these image quality parameters; the procedure was implemented in a suitable software and tested on high resolution imagery acquired by the QuickBird, WorldView-1 and Cartosat-1 satellites.

No MeSH data available.


Related in: MedlinePlus