The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
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2. STEREO ORTHOKIT DATA PRODUCTS 
Data products from the Fore and Aft sensors of Cartosat-1 are 
being operationally generated and disseminated to users from 
the National Remote Sensing Agency (NRSA), Hyderabad, 
India among others. Out of the many levels of products, the 
following three types are especially suited for the commercially- 
off-the-shelf (COTS) available photogrammetric software 
packages to support. 
1. Standard Mono Products 
2. Orthokit Mono Products 
3. Orthokit Stereo Products 
The orthokit stereo products are described in little more detail in 
the following subsection. Image data is by default in GeoTIFF 
format based on the Tagged Image File Format (TIFF) which is 
widely used today. This format is supported by all commercial 
software and is therefore easy to integrate. The Geographic 
extension (Geo) part of the format is supported by all 
photogrammetric software packages. 
The Geo part of GeoTIFF basically adds geo-referencing 
information from the image file to the TIFF file (geographic 
coordinates of the top-left comer and pixel sizes) and may also 
specify the map projection and geodetic system. 
2.1 Orthokit Stereo Products 
contain a pair of radiometrically corrected 10-bit image files 
corresponding to the Fore and Aft sensors in GeoTIFF format, 
two (encrypted and decrypted) ASCII files containing the 
rational polynomial coefficients (RPCs) respectively for each 
image, and metadata files in ASCII format. These products 
enable further processing to generate an orthoimage by way of 
improving the ground-to-image relationships as provided in the 
RPC files using ground control points (GCPs). 
Orthokit products are geometrically uncorrected except for the 
tagging of centre and comer coordinates with system corrected 
geographic latitude-longitude values. However detailed ground- 
to-image relationship(s) is (are) explicitly provided in the RPC 
file(s). 
3. ANOMALIES REPORTED 
More than two investigators consistently reported that Fore 
images supplied were somewhat blurred as compared to the Aft 
images, even while investigating different test sites. In certain 
cases, it was observed that the rational polynomial coefficients 
supplied were having the divide-by-zero anomaly resulting in 
inconsistencies in geometric processing. Also, in one of the test 
sites, the 0-360 degrees longitude convention adopted was 
found to result in software failures at user end. These anomalies 
have since been rectified. In the case of geometric anomalies, it 
was necessary to rectify the problem and provide corrected data 
sets to all users including those who faced these problems on a 
quick turn-around-time basis. The radiometric anomaly was not 
fixed immediately as it required a long lead time. Subsequent 
sections describe how these improvements were incorporated. 
4. IMPROVEMENTS IN RADIOMETRY 
Improvements in radiometry could be realised primarily based 
on the improved point spread function estimates provided by the 
payload design team from Space Applications Centre, ISRO for 
both the Fore and Aft sensors, subsequent to the C-SAP launch. 
However, the improvement process was not straight forward, as 
our attempts to improve radiometry, in addition to enhancing 
the basic image signals also enhanced the inherent noises 
present in the image signal. 
4.1 Restoration & Denoising: 
On analysing the specific phase-I data sets as well as other 
phase-II data sets of C-SAP test sites, the major source of noise 
signals were observed to be due to the residual uncorrected 
stagger component, especially in Fore images. Stagger 
correction is incorporated primarily to take care of the five 
pixels shift between odd and even detector elements in the focal 
plane of the CCD (charge-coupled device) detector arrays used 
in the Fore and Aft sensors. It has been observed that in certain 
cases, the standard algorithm for stagger correction for stitching 
the odd and even pixels of a scanline together to form a single 
full scanline was not performing adequately. 
4.1.1 Scene-based stagger removal: 
The stagger value between odd and even pixels changes scene 
to scene depending on the latitude and the variation of the 
dynamic component of the orbit and attitude values (like rate 
component). During the data pre processing (radiometric 
correction), the stagger value is computed using the ephemeris 
and is used for the alignment of the pixels. The sampling 
interval (125 ms) for attitude and orbital elements in the 
ancillary information is not sufficient to characterize the 
satellite behavior for smaller intervals of time such as stagger 
induced time difference for acquiring odd and even pixels of a 
scanline (5 scans or 1.83 ms). During the careful inspection of 
radiometric corrected image at the larger scales, the residual 
stagger effects can be seen to an extent for which small 
additional correction is required. This residual stagger must 
have been due to the inadequate sampling interval of the attitude 
information. 
The scene-based estimation of stagger can be done using 
relative control points (RCP) between the odd and even images. 
RCPs can be derived using digital cross correlation based image 
matching technique between the odd and even images. 
First the data set is prepared for correlated RCPs at every scan 
line. The differences in odd and even data are supposed to be 
the stagger in the raw image. A histogram approach is adopted 
to quantify the stagger number in along track direction for one 
thousand samples. The RCPs are generated at 12 positions in 
across track direction viz. pixel numbers 50, 500, 1000, 1500, 
2000, 2500, 3000, 3500, 4000, 4500, 5000, and 5500 with one 
scan sampling interval in along track direction. 
4.1.2 Candidate artifact zones identification & 
preprocessing: 
As the MTF correction process or restoration behaves in a 
peculiar way at high reflectance regions and high gradient 
regions in the form of ringing effects (alternate dark and bright 
lines) and false shadows (dark lines/ spots), these candidate 
artifact zones are first identified and locally pre-processed so 
that after restoration, no such artifacts are really present. 
Pre-processing involves detection and smoothing of high 
reflectance objects prior to the process of restoration. Automatic 
detection of bright objects in the original radiometrically 
corrected image is achieved by a tree-based segmentation 
approach. An image typically consists of several objects 
(features) placed over slowly varying background. In the