Thanks very much for your reply,Jordi.

I have read the first paper, it need cloud and cloud shadow match, and the 
processing was more complicated than OTB.

As refer to OTB cloud detection method,I have another question:the OTB 
cloud-detect method need specify a pixel which possibly is cloud, that 
means it can not recognize cloud automatically.If someone adopt the OTB 
cloud detection method to process large amount of images or run real-time 
on-board the remote sensing satellite, Obviously, one can not pick a cloud 
pixel for the OTB program.So my question is:

*Does there any techniques to determine the reference cloud spectral angle 
automatically? Or could I just preset the reference cloud spectral angle?*

I know that some methods such as SVM  could train the *cloud spectral 
angle *classifier which could act as a reference,Any other suggestion??

Thanks again!




On Thursday, March 5, 2015 at 12:37:58 PM UTC, Jordi Inglada wrote:
>
> [email protected] <javascript:> wrote: 
> > 
> > Hello guys, 
> > 
> > Now I am a beginner to use the OTB and I have some problems when using 
> > the Cloud Detection Example. 
> > 
> > As far as I know that there are several techniques to detect cloud 
> > from the remote sensing imagery. In the OTB, it detects the cloud 
> > based on spectral angle principle and assume that the image have four 
> > spectral bands. In my mind the parameter setting should affect the 
> > detection result, and the parameters must set according to Sensor that 
> > the camera adopted.But not every cameras have four spectral bands. 
> > 
> > So My questions are: 
> > 
> > Does there any papers about the OTB Cloud Detection method? 
> > 
> > Does it work well using only three spectral band? 
> > 
> > What is the basic principle to set the parameters? 
> > 
> > Anyone any suggestion is welcome! 
> > 
> > Thanks very much. 
> > 
> > -- 
>
> Hi, 
>
> You are right about the fact that there are many methods for the detection 
> of clouds. The spectral method proposed in OTB is a very simple one 
> (spectral angle and low-pass filtering before thresholding), but has the 
> advantage of not needing any particular spectral band (SWIR or thermal, for 
> instance). 
>
> If you want more sophisticated approaches, you should try to implement 
> something inspired from Fmask[1] for single-date acquisitions or from 
> MACCS[2] for multi-temporal series. 
>
> Jordi 
>
> [1] Zhu, Zhe, and Curtis E. Woodcock. "Object-based cloud and cloud shadow 
> detection in Landsat imagery." Remote Sensing of Environment 118 (2012): 
> 83-94. 
>
> [2] Hagolle, Olivier, et al. "A multi-temporal method for cloud detection, 
> applied to FORMOSAT-2, VENµS, LANDSAT and SENTINEL-2 images." Remote 
> Sensing of Environment 114.8 (2010): 1747-1755. 
>
>

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