Interpolation and combination rules for the temporal and spatial enhancement of SEVIRI and MODIS thermal image sequences

Summary Objectives: Modern tomographic imaging devices enable the acquisition of spatial and temporal image sequences. But, the spatial and temporal resolution of such devices is limited and therefore image interpolation techniques are needed to represent images at a desired level of discretization. This paper presents a method for structure-preserving interpolation between neighboring slices in temporal or spatial image sequences. Methods: In a first step, the spatiotemporal velocity field between image slices is determined using an optical flow-based registration method in order to establish spatial correspondence between adjacent slices. An iterative algorithm is applied using the spatial and temporal image derivatives and a spatiotemporal smoothing step. Afterwards, the calculated velocity field is used to generate an interpolated image at the desired time by averaging intensities between corresponding points. Three quantitative measures are defined to evaluate the performance of the interpolation method. Results: The behaviorand capability of the algorithm is demonstrated by synthetic images. A population of 17 temporal and spatial image sequences are utilized to compare the optical flow-based interpolation method to linear and shape-based interpolation. The quantitative results show that the optical flow-based method outperforms the linear and shape-based interpolation statistically significantly. Conclusions: The interpolation method presented is able to generate image sequences with appropriate spatial or temporal resolution needed for image comparison, analysis or visualization tasks. Quantitative and qualitative measures extracted from synthetic phantoms and medical image data show that the new method definitely has advantages over linear and shape-based interpolation.

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Tear Film Thermal Image Characteristics Analysis in Temporal and Spatial Aspects

Human Eye Imaging and Modeling ◽

10.1201/b12081-13 ◽

2012 ◽

pp. 169-184

Keyword(s):

Tear Film ◽

Thermal Image ◽

Image Characteristics ◽

Characteristics Analysis ◽

Temporal And Spatial

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Thermal image sequences for natural background modeling

10.1117/12.160543 ◽

1993 ◽

Cited By ~ 1

Author(s):

Jan S. de Vries ◽

Henk A. Lensen ◽

Abraham J. Maas

Keyword(s):

Background Modeling ◽

Thermal Image ◽

Image Sequences ◽

Natural Background

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Detection of lies by facial thermal imagery analysis

Revista Facultad de Ingeniería ◽

10.19053/01211129.v26.n44.2017.5771 ◽

2017 ◽

Vol 26 (44) ◽

pp. 45

Author(s):

Sebastián Bedoya-Echeverry ◽

Hernán Belalcázar-Ramírez ◽

Humberto Loaiza-Correa ◽

Sandra Esperanza Nope-Rodríguez ◽

Carlos Rafael Pinedo-Jaramillo ◽

...

Keyword(s):

Blood Flow ◽

Vision System ◽

Lie Detection ◽

Thermal Image ◽

Image Sequences ◽

Physical Contact ◽

Artificial Vision ◽

Physiological Changes ◽

Alternative Technique ◽

Flow Through

An artificial vision system is presented for lie detection by analyzing face thermal image sequences. This system represents an alternative technique to the polygraph. Some of its features are: 1) it has no physical contact with the examinee, 2) it is non-intrusive, 3) it has a potential for private use, and 4) it can simultaneously analyze several persons. The proposed system is based on the detection of physiological changes in temperature in the lacrimal puncta area caused by the subtle increase in blood flow through the nearby vascular network. These changes take place when anxiety appears as a consequence of deception. Thus, the system segments the periorbital area, and tracks consecutive frames using the Kanade-Lucas-Tomasi algorithm. The results show a success rate of 79.2 % in detecting lies using a simple classification based on the comparison between the estimated temperatures in control questions, and the rest of the interrogation procedure. The performance of this system is comparable with previous works, where cameras with better specifications were used.

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