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New modules of the software package “PHOTOMOD Radar” September 2010, Gaeta, Italy X th International Scientific and Technical Conference From Imagery to.

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Presentation on theme: "New modules of the software package “PHOTOMOD Radar” September 2010, Gaeta, Italy X th International Scientific and Technical Conference From Imagery to."— Presentation transcript:

1 New modules of the software package “PHOTOMOD Radar” September 2010, Gaeta, Italy X th International Scientific and Technical Conference From Imagery to Map: Digital Photogrammetric Technologies Roman I. Shuvalov

2 PHOTOMOD Radar. PHOTOMOD Radar. What’s new? Images Coherent Coregistration Tool 1 2 Image Quality Estimation Tools Target Response Analysis Target Response Analysis Radiometric Errors Analysis Radiometric Errors Analysis Geometric Errors Analysis Geometric Errors Analysis Image Statistics Analysis Image Statistics Analysis

3 Coherent coregistration & Joint processing Images Coherent Coregistration Tool Images loading Coregistration Joint thematic processing PHOTOMOD Radar Images Coherent Coregistration Tool “Images Coherent Coregistration Tool” has an embedded classificator and tools for coregistered images joint visualization. Pixels classification Coherence evolution analysis Differential interferometry Others… The joint processing may be: Permanent scatterers interferometry Multilooking

4 Images Coherent Coregistration Tool Interface of the software “Images Coherent Coregistration” The tool “Images Coherent Coregistration” allows to coregistrate radar images automatically with subpixel accuracy.

5 Images Coherent Coregistration Tool 1) spatial coregistration of the set of SAR images, 2) joint visualization, 3) pixel statistics estimation, 4) pixel classification. “Images Coherent Coregistration Tool” is intended for the joint processing of the set of radar images: The input data are: - interferometric set of SAR complex images.

6 Images Coherent Coregistration Tool The output data are: - interferometric set of coregistered SAR complex images, - amplitude image with increased radiometric resolution, - mean coherence image that characterizes changes of the underlying surface, - amplitude stability image that characterizes the stability of the backscattered signal power, - result of pixels classification.

7 Images Coherent Coregistration Tool Characteristics time Input set of images Classes Images loading and sorting Coherent coregistration Overlapping region calculation Pixel statistics estimation Pixel classification Sequence of processing steps

8 Images Coherent Coregistration Tool time Tab “Images” is intended for input data loading and sorting.

9 Images Coherent Coregistration Tool Coregistration settings dialog Tab “Coregistering” is intended for input images coregistration. There are two coregistration methods: manual and automatic.

10 Images Coherent Coregistration Tool Mean amplitude: Amplitude stability: Mean coherence: Tab “Multilooking” is intended for pixel numerical characteristics estimation.

11 Amplitude stability Mean amplitude Images Coherent Coregistration Tool

12 Mean coherence Pseudocolor representation of the estimated pixel characteristics: Amplitude stability  Red channel, Mean amplitude  Green channel, Mean coherence  Blue channel. Images Coherent Coregistration Tool

13 Pseudocolor representation of the estimated pixel characteristics: Amplitude stability  Red channel, Mean amplitude  Green channel, Mean coherence  Blue channel.

14 Images Coherent Coregistration Tool Pseudocolor representation of the estimated pixel characteristics: Amplitude stability  Red channel, Mean amplitude  Green channel, Mean coherence  Blue channel.

15 NameDescriptionColorInterpretation Class 1Low amplitude, high amplitude stability, low coherence. Radar shadow. Class 2Low amplitude, high amplitude stability, high coherence. Pavement. Class 3High amplitude, temperate amplitude stability, temperate coherence. Buildings and metallic constructions. Front slopes of the hills and opposite slopes of ravines. Class 4High amplitude, high amplitude stability, high coherence. Strong permanent scatterers. Class 5Low amplitude, low amplitude stability, temperate coherence. Water surface. Class 6Low amplitude (less than for class 7), temperate amplitude stability, temperate coherence (higher than for class 7). Vegetation. Class 7Low amplitude (higher than for class 6), temperate amplitude stability, temperate coherence (less than for class 6). Water surface surroundings. Pseudocolors interpretation Images Coherent Coregistration Tool

16 Radar shadow Front wall of the building Pavement Strong permanent scatterer Images Coherent Coregistration Tool Examples of objects

17 Images Coherent Coregistration Tool Patch of water surface Water surroundings Bridge over the river. Vegetation Examples of objects

18 Images Coherent Coregistration Tool Tab “Pseudocolor” allows to create pseudocolor composite image on the base of any three images of the input set.

19 Pseudocolor representation of three amplitude images. Images Coherent Coregistration Tool

20 Pseudocolor representation of three amplitude images.

21 Images Coherent Coregistration Tool Pseudocolor representation of three amplitude images.

22 Images Coherent Coregistration Tool Tab “Differences” allows to generate difference-images (or ratio-images) from the input set of images.

23 Pseudocolor representation of three amplitude difference- images. Images Coherent Coregistration Tool

24 Pseudocolor representation of three amplitude difference-images.

25 Images Coherent Coregistration Tool Tab “Classes” is intended for the image pixels classification. Two types of classification are available: amplitudes based and characteristics based.

26 Result of classification acquired using Bayes method on the base of Gauss model. Four classes dominate: blue (water surface, radar shadow), green (vegetation), brown (roads), and yellow (buildings). Images Coherent Coregistration Tool

27 Applications Land covers classification Change detection (coherent & incoherent) Image enhancement Ground subsidence monitoring

28 Image Quality Estimation Tools

29 Software tool for pulse response analysis Interface of the software tool “Pulse Response Analysis”. Estimated parameters are: 1) Local maximum location, 2) Peak power (dB), 3) Peak width (meters), 4) First zero location, 5) Second zero location, 6) First sidelobe location, 7) Pulse response mainlobe energy (dB), 8) First sidelobe energy, 9) Ratio of sidelobe energy to mainlobe energy, and some others… The tool “Pulse Response Analysis” allows getting target response profile on the image.

30 Software tool for pulse response analysis - mainlobe region - sidelobe region - noise region Pulse response function schematic view Pulse response on the SAR image Interpolated pulse response function 3D view of the interpolated pulse response function

31 Analysis option could be adjusted RADARSAT-1. Product type – SGX. Beam – F2. Interpolated profiles along range and azimuth Software tool for pulse response analysis

32 Report generated by the software tool. It contains results of SAR impulse response function analysis. Software tool for pulse response analysis

33 Software tool for geometric analysis Interface of the software tool “Image Geometry Analysis”. Estimated parameters are: 1) absolute location accuracy, 2) absolute geometric distortions, 3) relative geometric distortions The set of ground control points is required. The report in textual file is generated.

34 Geometric errors may be viewed and measured in the “Viewer”. Software tool for geometric analysis

35 Software tool for radiometric analysis Interface of the software tool “Image Radiometry Analysis”. Estimated parameters are: 1) relative radiometric error, 2) radiometric linearity, 3) range ambiguity level, 4) azimuth ambiguity level, 5) equivalent number of independent looks, 6) mean level of the additive noise. The report in textual file is generated.

36 Software tool for radiometric analysis Set of corner reflectors for radiometric linearity estimation Rectangular frame for equivalent number of independent looks estimating Rectangular frames for relative radiometric error estimating Input image Estimating of additive noise mean level

37 The dialog of the radiometric analysis settings Software tool for radiometric analysis

38 Azimuth ambiguity level estimating Object which gives strong backscattered signal Azimuth ambiguity zone The position of the ambiguity zone is calculated automatically.

39 Software tool for radiometric analysis Range ambiguity zone Object which gives strong backscattered signal Input image for the range ambiguity level estimation. On the sea surface in the left part of the image one can see range ambiguity spots. The strong backscattered signal from the mountain ridges in the right part of the image is laid over the weak signal from the sea surface. Range ambiguity level estimating Rectangular frames for range ambiguity level estimation. Dialog of the estimation settings The position of the ambiguity zone is calculated automatically.

40 Software tool for image statistics analysis Estimated parameters are: 1) maximum value on the image, 2) percent of pixels with maximum value, 3) minimum value on the image, 4) percent of pixels with minimum value, 5) image dynamic range, 6) peak histogram value, 7) mean value on the image, 8) standard deviation on the image. Interface of the software tool “Image Statistics Analysis”. The tool “Image Statistics Analysis” allows to draw histogram of the image and to estimate basic numeric characteristics of the image. The report in textual file is generated.

41 Image Quality Estimation Tools Possible applications SAR images quality control SAR image parameters estimation SAR image understanding PHOTOMOD Radar Image Quality Estimation Tools SAR image generation Image quality control Image thematic processing

42 Thank you for attention !


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