Orientation averaging of electron backscattered diffraction data

Humphreys, F.J.; Bate, Pete S.; Hurley, Peter

doi:10.1046/j.1365-2818.2001.00777.x

Cited by 182 publications

(117 citation statements)

References 14 publications

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“…And finally, for ELEE, HMF, SNN, Kuwahara, and the adaptive Wiener filters, a window size of 5 × 5 pixels was used in the numerical evaluation of these filters. This choice of window size for these filters is also commonly made in the literature [24][25][26][27][28][29][30][31][32][33][34][35][41][42][43][44][45]. On the other hand, for an OCT image to be filtered, the optimum choice of this window size should also take into account the residual correlation between two adjacent pixels of the OCT image.…”

Section: Introductionmentioning

confidence: 99%

Speckle reduction in optical coherence tomography images using digital filtering

et al. 2007

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Speckle noise is a ubiquitous artifact that limits the interpretation of optical coherence tomography images. Here we apply various speckle-reduction digital filters to optical coherence tomography images and compare their performance. Our results indicate that shift-invariant, nonorthogonal wavelet-transform-based filters together with enhanced Lee and adaptive Wiener filters can significantly reduce speckle and increase the signal-to-noise ratio, while preserving strong edges. The speckle reduction capabilities of these filters are also compared with speckle reduction from incoherent angular compounding. Our results suggest that by using these digital filters, the number of individual angles required to attain a certain level of speckle reduction can be decreased.

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Section: Introductionmentioning

confidence: 99%

Speckle reduction in optical coherence tomography images using digital filtering

et al. 2007

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“…Defining q GB Ͻ0.5°would be desirable in order to be in accordance with the result from the point counting method. However, this value is within the angular resolution of EBSP indexing (normally ϳ1°in conventional mapping 17) ) and could result in abnormal behavior in the process. Therefore, the grain boundary definition angle was set to 1.5°, even though the resulting martensite volume fraction is underestimated frequently.…”

Section: Description Of the Methodsmentioning

confidence: 98%

Phase Analysis of Steels by Grain-averaged EBSD Functions

et al. 2011

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EBSD mapping was used for phase analysis of multi-phase steels. Some products of austenite decomposition could be discriminated using a range of grain-average functions and properties derived from the map data. In DP steels, martensite could be extracted from the ferrite matrix using the average band contrast or a set of geographic information. Bainite in TRIP steel was identified with the local variations of band contrast and orientation inside a grain. As the proposed method reproduced a phase map, a visual confirmation of the result and additional analyses were possible.KEY WORDS: EBSD; phase analysis; steel; grain average function; DP steel; TRIP steel.separated unambiguously with a discrete threshold value. The result would be unreliable when there is considerable peak overlap. In addition, the result can indicate that both phases coexist in a single grain if a grain consists of pixels with PQ values similar to the threshold value, which is unreasonable in a metallurgical sense. Wu et al. dissociated the IQ profiles using several Gaussian peaks, each of which represented different phases. Subsequently, the volume fraction of each phase could be estimated from the peak area.13) This method can deal with the profiles of arbitrary shapes. However, the profile data is actually dissociated from the map data after the operation. Consequently, it is impossible to know the locations and orientations of the pixels that contribute to each Gaussian peak. Additional analyses, such as grain size measurements and texture evaluations for each phase, are not possible. The great potential of EBSD is underutilized in this case.In this study, an image-based method was developed for the phase analysis of steels that can fully exploit the EBSD mapping data. The applications to dual phase (DP) steel and transformation-induced plasticity (TRIP) steel are presented. Specimens and Experimental ConditionThe test materials were DP and TRIP steels with the composition of 0.06C-2.2Mn-1.0Si-0.02Mo-0.01Cr and 0.2C-1.8Mn-0.5Si, respectively. Cold rolled and intercritical-annealed samples were electro-polished with Struers Lectropol-5 at the final step of metallographic sample preparation. The electrolyte was 5% perchloric acid in ethanol. The electropolish was performed for 25 s at Ϫ20°C with the condition of 25V-20 flow rate.EBSD mapping was performed using a field emission scanning electron microscope (JSM-6500F) equipped with a HKL Nordlys II camera. Therefore, the quality of the pattern is represented by BC in this paper. The accelerating voltage, probe current and working distance was 20 kV, 4 nA and 15 mm, respectively, with the sample stage tilted by 70°. The camera resolution was 168ϫ128 pixels in operation of 8ϫ8 binning. The mapping grid was a regular square in 0.1 mm steps. FCC (austenite) and BCC iron (ferrite) were chosen as the input phases. Description of the MethodThe key feature of the methodology is to use various grain-average functions and properties for phase discrimination on a grain-by-grain basis. Although not clea...

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“…An approach to solve this thresholding problem is to use an edge-preserving lowpass filter to smooth the data. Humphreys et al [47] have implemented a Kuwahara filter, which reduces the noise in a data set by statistically analysing neighbourhoods surrounding every point. Each pixel is iteratively replaced with the average of the neighbourhood with the least variance.…”

Section: An Automated Methods For Reconstructing Various Types Of Bounmentioning

confidence: 99%

“…The highlighted microbands in figure 11b are isolated in 3D in figure 11c to show the nature of the interior of the segmentation. This data set was also segmented with the Kuwahara filter method [47]. It was found that, while this type of filter partially aligns with the visible microband structure, no threshold value was found to be appropriate for the entire data set, which was evidenced by the presence of both significant oversegmentation and undersegmentation.…”

Section: Microbands In Cold Rolled Aluminiummentioning

confidence: 99%

Uncovering the true nature of deformation microstructures using 3D analysis methods

Ferry

Quadir

Afrin

et al. 2015

IOP Conf. Ser.: Mater. Sci. Eng.

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Abstract. Three-dimensional electron backscatter diffraction (3D EBSD) has emerged as a powerful technique for generating 3D crystallographic information in reasonably large volumes of a microstructure. The technique uses a focused ion beam (FIB) as a high precision serial sectioning device for generating consecutive ion milled surfaces of a material, with each milled surface subsequently mapped by EBSD. The successive EBSD maps are combined using a suitable post-processing method to generate a crystallographic volume of the microstructure. The first part of this paper shows the usefulness of 3D EBSD for understanding the origin of various structural features associated with the plastic deformation of metals. The second part describes a new method for automatically identifying the various types of low and high angle boundaries found in deformed and annealed metals, particularly those associated with grains exhibiting subtle and gradual variations in orientation. We have adapted a 2D image segmentation technique, fast multiscale clustering, to 3D EBSD data using a novel variance function to accommodate quaternion data. This adaptation is capable of segmenting based on subtle and gradual variation as well as on sharp boundaries within the data. We demonstrate the excellent capabilities of this technique with application to 3D EBSD data sets generated from a range of cold rolled and annealed metals described in the paper.

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Orientation averaging of electron backscattered diffraction data

Cited by 182 publications

References 14 publications

Speckle reduction in optical coherence tomography images using digital filtering

Speckle reduction in optical coherence tomography images using digital filtering

Phase Analysis of Steels by Grain-averaged EBSD Functions

Uncovering the true nature of deformation microstructures using 3D analysis methods

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