Comparison of three ImageJ-tools for global orientation analysis
Locked
 
|
Dear ImageJ-listers and experts!
To my knowledge, there are three currently maintained ImageJ-tools (plugins or macros) that can perform *global* orientation analyses of images: 1. OrientationJ v2.0.4 and v16.01.2018 (macro-recordable ImageJ-plugin) <http://bigwww.epfl.ch/demo/orientation/#soft> 2. Directionality v2.3.0 (macro-recordable ImageJ-plugin) <https://imagej.net/Directionality> 3. Easy Orientation v2.0.0 (macro-wrapper of ImageJ-plugins) <https://www.gluender.de/Miscellanea/MiscTexts/UtilitiesText.html#Gl-2019-2> Since 2013 I've received quite some requests and seen quite some posts on the list and the forum, dealing with the question "What ImageJ-tools are best suited for *global* orientation analyses?" I've tried to answer and I've commented on this question in numerous contributions but they are scattered over several places. So here is the missing compilation... Before I start with quantitative comparisons, I should like to sketch the approaches (source code has not been inspected for this purpose): ----------------------------------------------------------------------- General: -------- 1. OrientationJ approach (tool: "Orientation Distribution")____________ -- In the first place, this plugin is meant for local orientation analyses based on "Structure Tensors". Global results (orientation histograms) are obtained by combining (weighted) results of the local analyses which is performed by the tool "Orientation Distribution". -- OrientationJ lets one choose from six kinds of "Structure Tensors". Their Gaussian windowed area of local operation can be specified (sigma). In the present context of global analyses, the "Fourier"-scheme and a Gaussian of sigma=1 lead to relative good results. -- The weighting of the locally obtained orientations during the process of their combination mainly depends on the parameter "Minimum Coherence". In the present context, 70% was found to be reasonable and is suggested by the authors as well. ("Min. Energy" = 10%) -- The angular range of analysis is always 180deg (-90 to +89; -89.5 to 89.5) with fixed angular resolution of 1deg. -- The scaling of the histogram values remains unexplained. -- In the histograms 0deg stands for the horizontal and the angle increases counter-clockwise. -- "Orientation Distribution" accepts images of rectangular support. -- "OrientationJ" is easily installed on ImageJ and Fiji. 2. Directionality approaches (both methods)____________________________ (a) Method: "Local Gradient Orientation" -- In this mode the plugin computes global orientation histograms from results of local analyses, in a similar fashion as the tool "Orientation Distribution" described above. -- Only a single local operator of fixed size is available. (b) Method: "Fourier components" -- In this mode the plugin computes global orientation histograms from results of (regional?) Fourier power-spectral analyses. -- The image or regions appear to be windowed and each power spectrum is summed in several blurred double-sectors centered on the spectral origin. Sums of rotated double-sectors give the histogram values, with the rotation angles plus 90deg as the histogram abscissa. -- The radial shape of the double-sectors realize a highpass of fixed transfer function. (a) & (b) -- The angular range of analysis and the angular resolution can be set by the user. The latter is done by specifying the desired number of histogram values. -- The scaling of the histogram values is as usual: The summed values add to one. -- In the histograms 0deg stands for the horizontal and the angle increases counter-clockwise. -- "Directionality" accepts images of rectangular support. -- "Directionality" comes with Fiji and is difficult to install on ImageJ. 3. Easy Orientation approach (tool: "Easy Orientation Analysis")_______ -- The approach is related to that of "Directionality (b)". It works purely global and is mathematically well-founded.* -- The image is windowed by a defined function and its DC-component is suppressed. -- The Fourier power-spectrum is summed along straight lines through its origin. The number of rotated lines depends on the image size and is individually determined according to the angular sampling theorem.** -- The power-spectral analysis is not restricted by any additional filters, although a highpass of a user-set cutoff frequency can optionally be applied. -- The angular range of analysis is always 180deg (0 to 180-delta) with image size-specific best angular resolution according to the angular sampling theorem. -- The scaling of the histogram values is as usual: The summed values add to one. -- In the histograms 0deg stands for the horizontal and the angle increases counter-clockwise. -- "Easy Orientation Analysis" always analyzes the largest square-sized and central area of an image. -- "Easy Orientation" is easily installed on ImageJ and Fiji. -- About verification and validation of this tool, please read: <http://imagej.1557.x6.nabble.com/info-on-directionality-plugin-tp5022022p5022074.html> *<www.gluender.de/Writings/WritingsTexts/HardText.html#Gl-1986-2> **<http://www.gluender.de/Writings/WritingsTexts/HardText.html#Gl-2013-1> ----------------------------------------------------------------------- Again: "What ImageJ-tools are best suited for global orientation analyses?" This question isn't easy to answer but what can be done, is to apply the above ImageJ-tools to the same test image, -- judge the quality of the result, -- estimate the relative speed of execution, and -- take into account individual features (see above). It appears obvious that there isn't a single test image that is suited for this task, i.e. that can represent all kinds of images *and* leads to results that can be judged objectively. Images for which the latter is possible, are those with (concentric) circular structures. Ideally, such images should show independence of orientation, i.e. a "flat" histogram. I've decided to use a radial chirp, i.e. a gray-level zone-plate having an 256x256 support (canvas). The maximum fundamental spatial frequency of this zone-plate is 2/3 of the Nyquist-frequency. For this image support the best angular resolution is obtained for 402 angles per 180deg or 403 angles per 181deg. -- Attached please find a ZIP-archive that contains the zone-plate image and six result plots (histograms). -- The relative deviation of the histogram values from their mean is denoted as "Coefficient of Variation" (CV) in percent. Ideally it should be zero. -- Execution times (T) in seconds are measured for a 1024x1024 zone-plate with the display of the histogram plot and the table of histogram values. Of course the times are machine-dependent, i.e. only the relations are of importance. Configuration for 1. and 3.: ImageJ 1.52p; Java 1.8.0_172; dedicated RAM 5 GB, 8 threads Configuration for 2.: Fiji 2.0.0-rc-69/1.52p; Java 1.8.0_202; dedicated RAM 5 GB, 8 threads ----------------------------------------------------------------------- Results: -------- 1. tool: "Orientation Distribution"____________________________________ I've considered two versions of this tool that, with the same parameter settings (see screen-shots), resulted in fairly different histograms: (a) OrientationJ-v204_OJ-Histogram.png (b) OrientationJ-v16012018_S-Distribution.png (a) CV = 5.13 % (180 values; T ≈ 1.060 s (180 values); (b) CV = 1.58 % (180 values; T ≈ 0.950 s (180 values); Comments: -- Reasons for the different results of the two versions are unclear. -- Regarding the execution times one should bear in mind that they are for computations of 180 values *only*. -- It is by no means clear which parameter setting gives optimum global results and why. 2. tool: "Directionality"______________________________________________ I've set the angular range of analysis to the default (-90 to 90) and the number of histogram values to 403 and for (b) additionally to 181. The resulting histograms are: (a) Directionality-230_LocalGradientOrient-Histogram_403.png (b) Directionality-230_FourierComponents-Histogram_403.png Directionality-230_FourierComponents-Histogram_181.png (a) CV = 40.16 % (403 values); T ≈ 0.275 s (1609 values); (b) CV = 27.97 % (403 values); T ≈ 64.5 s (1609 values);* CV = 12.19 % (181 values); T ≈ 7.1 s (181 values); *needs more than 5 GB of dedicated RAM (runs with 9 GB) Comments: -- Reasons for the poor CVs are unclear. -- Reasons for the enormous processing time and memory consumption of approach (b) are unclear but may be caused by sub-optimum source code. -- The appearance of the original histograms (not shown here) is questionable. Every bin appears to have a distracting gray shadow and it is difficult to obtain a display size that provides a regular (gap-less) bin-arrangement. The fitted curve makes little sense. 3. tool: "Easy Orientation Analysis"___________________________________ The number of histogram values is automatically set according to the angular sampling theorem. No highpass is applied. The resulting histograms is: EasyOrientation-200_Orientation Salience.png CV = 0.068 % (402 values); T ≈ 1.020 s (1608 values); Comment: -- For many natural images the cutoff frequency of an optional highpass is crucial. "Easy Orientation Analysis" provides this option and the companion tool "Orientation Highpass Test" facilitates the choice of an adequate cutoff. ----------------------------------------------------------------------- As always, please perform your own tests and form your own opinion about the tools. Regards Herbie -- Sent from: http://imagej.1557.x6.nabble.com/ -- ImageJ mailing list: http://imagej.nih.gov/ij/list.html |
|
|
Attached please find the missing ZIP-archive with the histogram-results.
Histograms.zip <http://imagej.1557.x6.nabble.com/file/t380516/Histograms.zip> Herbie wrote > Dear ImageJ-listers and experts! > > To my knowledge, there are three currently maintained ImageJ-tools > (plugins > or macros) that can perform *global* orientation analyses of images: > > 1. OrientationJ v2.0.4 and v16.01.2018 (macro-recordable ImageJ-plugin) > <http://bigwww.epfl.ch/demo/orientation/#soft> > > 2. Directionality v2.3.0 (macro-recordable ImageJ-plugin) > <https://imagej.net/Directionality> > > 3. Easy Orientation v2.0.0 (macro-wrapper of ImageJ-plugins) > <https://www.gluender.de/Miscellanea/MiscTexts/UtilitiesText.html#Gl-2019-2> > > Since 2013 I've received quite some requests and seen quite some posts on > the list and the forum, dealing with the question > "What ImageJ-tools are best suited for *global* orientation analyses?" > I've tried to answer and I've commented on this question in numerous > contributions but they are scattered over several places. So here is the > missing compilation... > > Before I start with quantitative comparisons, I should like to sketch the > approaches (source code has not been inspected for this purpose): > > ----------------------------------------------------------------------- > General: > -------- > > 1. OrientationJ approach (tool: "Orientation Distribution")____________ > -- In the first place, this plugin is meant for local orientation analyses > based on "Structure Tensors". Global results (orientation histograms) are > obtained by combining (weighted) results of the local analyses which is > performed by the tool "Orientation Distribution". > -- OrientationJ lets one choose from six kinds of "Structure Tensors". > Their > Gaussian windowed area of local operation can be specified (sigma). In the > present context of global analyses, the "Fourier"-scheme and a Gaussian of > sigma=1 lead to relative good results. > -- The weighting of the locally obtained orientations during the process > of > their combination mainly depends on the parameter "Minimum Coherence". In > the present context, 70% was found to be reasonable and is suggested by > the > authors as well. ("Min. Energy" = 10%) > -- The angular range of analysis is always 180deg (-90 to +89; -89.5 to > 89.5) with fixed angular resolution of 1deg. > -- The scaling of the histogram values remains unexplained. > -- In the histograms 0deg stands for the horizontal and the angle > increases > counter-clockwise. > -- "Orientation Distribution" accepts images of rectangular support. > -- "OrientationJ" is easily installed on ImageJ and Fiji. > > 2. Directionality approaches (both methods)____________________________ > (a) Method: "Local Gradient Orientation" > -- In this mode the plugin computes global orientation histograms from > results of local analyses, in a similar fashion as the tool "Orientation > Distribution" described above. > -- Only a single local operator of fixed size is available. > (b) Method: "Fourier components" > -- In this mode the plugin computes global orientation histograms from > results of (regional?) Fourier power-spectral analyses. > -- The image or regions appear to be windowed and each power spectrum is > summed in several blurred double-sectors centered on the spectral origin. > Sums of rotated double-sectors give the histogram values, with the > rotation > angles plus 90deg as the histogram abscissa. > -- The radial shape of the double-sectors realize a highpass of fixed > transfer function. > (a) & (b) > -- The angular range of analysis and the angular resolution can be set by > the user. The latter is done by specifying the desired number of histogram > values. > -- The scaling of the histogram values is as usual: The summed values add > to > one. > -- In the histograms 0deg stands for the horizontal and the angle > increases > counter-clockwise. > -- "Directionality" accepts images of rectangular support. > -- "Directionality" comes with Fiji and is difficult to install on ImageJ. > > 3. Easy Orientation approach (tool: "Easy Orientation Analysis")_______ > -- The approach is related to that of "Directionality (b)". It works > purely > global and is mathematically well-founded.* > -- The image is windowed by a defined function and its DC-component is > suppressed. > -- The Fourier power-spectrum is summed along straight lines through its > origin. The number of rotated lines depends on the image size and is > individually determined according to the angular sampling theorem.** > -- The power-spectral analysis is not restricted by any additional > filters, > although a highpass of a user-set cutoff frequency can optionally be > applied. > -- The angular range of analysis is always 180deg (0 to 180-delta) with > image size-specific best angular resolution according to the angular > sampling theorem. > -- The scaling of the histogram values is as usual: The summed values add > to > one. > -- In the histograms 0deg stands for the horizontal and the angle > increases > counter-clockwise. > -- "Easy Orientation Analysis" always analyzes the largest square-sized > and > central area of an image. > -- "Easy Orientation" is easily installed on ImageJ and Fiji. > -- About verification and validation of this tool, please read: > <http://imagej.1557.x6.nabble.com/info-on-directionality-plugin-tp5022022p5022074.html> > > *<www.gluender.de/Writings/WritingsTexts/HardText.html#Gl-1986-2> > **<http://www.gluender.de/Writings/WritingsTexts/HardText.html#Gl-2013-1> > ----------------------------------------------------------------------- > > Again: > "What ImageJ-tools are best suited for global orientation analyses?" > > This question isn't easy to answer but what can be done, is to apply the > above ImageJ-tools to the same test image, > -- judge the quality of the result, > -- estimate the relative speed of execution, and > -- take into account individual features (see above). > > It appears obvious that there isn't a single test image that is suited for > this task, i.e. that can represent all kinds of images *and* leads to > results that can be judged objectively. > > Images for which the latter is possible, are those with (concentric) > circular structures. Ideally, such images should show independence of > orientation, i.e. a "flat" histogram. > > I've decided to use a radial chirp, i.e. a gray-level zone-plate having an > 256x256 support (canvas). The maximum fundamental spatial frequency of > this > zone-plate is 2/3 of the Nyquist-frequency. For this image support the > best > angular resolution is obtained for 402 angles per 180deg or 403 angles per > 181deg. > > -- Attached please find a ZIP-archive that contains the zone-plate image > and > six result plots (histograms). > -- The relative deviation of the histogram values from their mean is > denoted > as "Coefficient of Variation" (CV) in percent. Ideally it should be zero. > -- Execution times (T) in seconds are measured for a 1024x1024 zone-plate > with the display of the histogram plot and the table of histogram values. > Of > course the times are machine-dependent, i.e. only the relations are of > importance. > > Configuration for 1. and 3.: > ImageJ 1.52p; Java 1.8.0_172; dedicated RAM 5 GB, 8 threads > Configuration for 2.: > Fiji 2.0.0-rc-69/1.52p; Java 1.8.0_202; dedicated RAM 5 GB, 8 threads > > > ----------------------------------------------------------------------- > Results: > -------- > > 1. tool: "Orientation Distribution"____________________________________ > I've considered two versions of this tool that, with the same parameter > settings (see screen-shots), resulted in fairly different histograms: > (a) OrientationJ-v204_OJ-Histogram.png > (b) OrientationJ-v16012018_S-Distribution.png > > (a) CV = 5.13 % (180 values; T ≈ 1.060 s (180 values); > (b) CV = 1.58 % (180 values; T ≈ 0.950 s (180 values); > > Comments: > -- Reasons for the different results of the two versions are unclear. > -- Regarding the execution times one should bear in mind that they are for > computations of 180 values *only*. > -- It is by no means clear which parameter setting gives optimum global > results and why. > > > 2. tool: "Directionality"______________________________________________ > I've set the angular range of analysis to the default (-90 to 90) and the > number of histogram values to 403 and for (b) additionally to 181. The > resulting histograms are: > (a) Directionality-230_LocalGradientOrient-Histogram_403.png > (b) Directionality-230_FourierComponents-Histogram_403.png > Directionality-230_FourierComponents-Histogram_181.png > > (a) CV = 40.16 % (403 values); T ≈ 0.275 s (1609 values); > (b) CV = 27.97 % (403 values); T ≈ 64.5 s (1609 values);* > CV = 12.19 % (181 values); T ≈ 7.1 s (181 values); > > *needs more than 5 GB of dedicated RAM (runs with 9 GB) > > Comments: > -- Reasons for the poor CVs are unclear. > -- Reasons for the enormous processing time and memory consumption of > approach (b) are unclear but may be caused by sub-optimum source code. > -- The appearance of the original histograms (not shown here) is > questionable. Every bin appears to have a distracting gray shadow and it > is > difficult to obtain a display size that provides a regular (gap-less) > bin-arrangement. The fitted curve makes little sense. > > > 3. tool: "Easy Orientation Analysis"___________________________________ > The number of histogram values is automatically set according to the > angular > sampling theorem. No highpass is applied. The resulting histograms is: > EasyOrientation-200_Orientation Salience.png > > CV = 0.068 % (402 values); T ≈ 1.020 s (1608 values); > > Comment: > -- For many natural images the cutoff frequency of an optional highpass is > crucial. "Easy Orientation Analysis" provides this option and the > companion > tool "Orientation Highpass Test" facilitates the choice of an adequate > cutoff. > ----------------------------------------------------------------------- > > As always, please perform your own tests and form your own opinion about > the > tools. > > Regards > > Herbie > > > > -- > Sent from: http://imagej.1557.x6.nabble.com/ > > -- > ImageJ mailing list: http://imagej.nih.gov/ij/list.html -- Sent from: http://imagej.1557.x6.nabble.com/ -- ImageJ mailing list: http://imagej.nih.gov/ij/list.html |
«
Return to ImageJ
|
1 view|%1 views
| Free forum by Nabble | Edit this page |