[Gdaldev] GCP's, Warping and Source Data Projections

看到这么一节问题不是很明白，那位搞遥感方面的高人给大概解释一下关键部分？

还有几个疑问：

1、GDAL能做几何精校正（Precise Geometry Rectification）吗？

2、下边的帖子中作者似乎是说GDAL只提供了多项式纠正的方式，其他方式尚没有实现，是不是这样？因为我看GDALWarp 的API只看到有设置采样方法的地方，没有看到设置纠正函数的地方。

3、另外，个人理解GDALWarp中的栅格重投影和几何精纠正的在实现机制是一样的，只是重投影用的是投影转换来确定的转换参数，和几何纠正的区别仅在于转换参数的求取方法不同。不知对否？

 

Ethan Alpert ealpert at digitalglobe.com
Thu Sep 16 22:04:35 EDT 2004

Well I've done some good GDAL库 documentation reading in the past couple days trying to get a handle on what I'm trying to do with respect to GDAL库's data model and I'm left with more questions than answers.



I've boiled them down to one which if I can get a handle on I might be to conceptually work my way through the rest.



Being pretty ignorant I figured that GDAL库's GCP's support could infer a projection.  Which means I believed that by providing geographic coordinates and pixel/line coordinates that GDAL库 would some how infer a custom projection for my input data.



Is this truly a misconception?



The documentation for GDALCreateGenImgProjTransformer seems to suggest this but I can't really find any references to how GCPs need to be related spatially for it to work or whether my source needs to be in a known projection.



My data is reduced resolution raw satellite imagery. By raw I mean there's been no ortho-rectification. In real world coordinates my pixel size can vary a lot. 



I do have lots of useful information about my data. I have ephemeris, attitude, bearing angle and off nadir angle data. I also have anywhere from 4 to 40 geographic coordinates that define the polygon of the strip (my GCP's) depending on the length of the strip. Each strip can often bend and stretch through out it's scan.



So anyway it seems to me I have enough to define a unique projection for each strip of satellite imagery. My question is do I really need to go through all of this? I'm not looking for the most accurate projection but I'm looking for a better way to do it than I am currently.



So the utility gdalwarp doesn't like my GCP's for higher order warping and produces an awkwardly placed warped image when using -order 1.  The only thing I can think of is that I have some misconception of how to classify my data's coordinate system,  I'm doing something wrong with preparing it or I need to look into the utility that initially generated the 4-40 GCP's of this data.



Thanks,



-ethan





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[Gdal-dev] GCP's, Warping and Source Data Projections

Frank Warmerdam warmerdam at pobox.com
Thu Sep 16 23:15:03 EDT 2004 
Ethan Alpert wrote:

> Being pretty ignorant I figured that GDAL库's GCP's support could infer a 

> projection.  Which means I believed that by providing geographic 

> coordinates and pixel/line coordinates that GDAL库 would some how infer a 

> custom projection for my input data.

>  

> Is this truly a misconception?


Ethan,
I'm not sure what you mean by this.  Certainly GDAL库 does not have any

mechanism to take a set of pixel/line to lat/long GCPs and from them

infer a projected coordinate system appropriate for the image.



However, given GCPs you should be able to rectify or even reproject

the image to some new coordinate system.  The caveat is that the

available low order polynomials behave very poorly for "interesting"

image geometries.



What you really need for raw image views that include a substantial

chunk of the globe is:

1) a real projection that describes the geometry of the image.  For

instance the "space oblique mercator" (as I understand it) is a

projection that describes the geometry of scenes taken from

satellites like landsat.  If you could describe your image in terms

of a valid projection you could use gdalwarp to warp it accurately.



2) a better GCP based trasnformation function than low order polynomials.

When I was at PCI we had a transformation called thin-plate splines.
I didn't really understand the math of it, but basically there
were terms in the equation for each GCP provided and it was an
exact transformation at the GCPs and it varied "smoothly and
reasonably" between the GCPs.  If you had decent GCP coverage for
an image it would give you as well behaved warp.  Other rubber sheeting

approaches might also work similarly.
GDAL库 unfortunately lacks any such transfomration that works smoothly

for complex geometries.  This is definately an area I would like to improve

GDAL库.  Any deeper minds than mine interested in working on that are welcome!

Certainly papers exist in the literature for a variety of good rubber sheeting

methods, but I have not had the time, patience or mathematical depth to apply

them.



Best regards,

-- 

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原文地址：https://www.cnblogs.com/flyingfish/p/865653.html