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Angel D. Sappa; Juan A. Carvajal; Cristhian A. Aguilera; Miguel Oliveira; Dennis G. Romero; Boris X. Vintimilla |
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Title |
Wavelet-Based Visible and Infrared Image Fusion: A Comparative Study |
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Journal Article |
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Year |
2016 |
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Sensors Journal |
Abbreviated Journal |
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Vol. 16 |
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pp. 1-15 |
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Keywords |
image fusion; fusion evaluation metrics; visible and infrared imaging; discrete wavelet transform |
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Abstract |
This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and LongWave InfraRed (LWIR). |
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no |
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cidis @ cidis @ |
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47 |
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Author |
Angel D. Sappa; Cristhian A. Aguilera; Juan A. Carvajal Ayala; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla; Ricardo Toledo |
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Title |
Monocular visual odometry: a cross-spectral image fusion based approach |
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Journal Article |
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Year |
2016 |
Publication |
Robotics and Autonomous Systems Journal |
Abbreviated Journal |
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Vol. 86 |
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pp. 26-36 |
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Keywords |
Monocular visual odometry LWIR-RGB cross-spectral imaging Image fusion |
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Abstract |
This manuscript evaluates the usage of fused cross-spectral images in a monocular visual odometry approach. Fused images are obtained through a Discrete Wavelet Transform (DWT) scheme, where the best setup is em- pirically obtained by means of a mutual information based evaluation met- ric. The objective is to have a exible scheme where fusion parameters are adapted according to the characteristics of the given images. Visual odom- etry is computed from the fused monocular images using an off the shelf approach. Experimental results using data sets obtained with two different platforms are presented. Additionally, comparison with a previous approach as well as with monocular-visible/infrared spectra are also provided showing the advantages of the proposed scheme. |
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no |
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cidis @ cidis @ |
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54 |
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Author |
Cristhian A. Aguilera, Cristhian Aguilera, Cristóbal A. Navarro, & Angel D. Sappa |
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Title |
Fast CNN Stereo Depth Estimation through Embedded GPU Devices |
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Journal Article |
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2020 |
Publication |
Sensors 2020 |
Abbreviated Journal |
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Vol. 2020-June |
Issue |
11 |
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pp. 1-13 |
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Keywords |
stereo matching; deep learning; embedded GPU |
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Abstract |
Current CNN-based stereo depth estimation models can barely run under real-time
constraints on embedded graphic processing unit (GPU) devices. Moreover, state-of-the-art
evaluations usually do not consider model optimization techniques, being that it is unknown what is
the current potential on embedded GPU devices. In this work, we evaluate two state-of-the-art models
on three different embedded GPU devices, with and without optimization methods, presenting
performance results that illustrate the actual capabilities of embedded GPU devices for stereo depth
estimation. More importantly, based on our evaluation, we propose the use of a U-Net like architecture
for postprocessing the cost-volume, instead of a typical sequence of 3D convolutions, drastically
augmenting the runtime speed of current models. In our experiments, we achieve real-time inference
speed, in the range of 5–32 ms, for 1216 368 input stereo images on the Jetson TX2, Jetson Xavier,
and Jetson Nano embedded devices. |
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14248220 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
132 |
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Author |
Cristhian A. Aguilera; Angel D. Sappa; R. Toledo |
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Title |
LGHD: A feature descriptor for matching across non-linear intensity variations |
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Conference Article |
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Year |
2015 |
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IEEE International Conference on, Quebec City, QC, 2015 |
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178 - 181 |
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Keywords |
Feature descriptor, multi-modal, multispectral, NIR, LWIR |
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Abstract |
This paper presents a new feature descriptor suitable to the task of matching features points between images with nonlinear intensity variations. This includes image pairs with significant illuminations changes, multi-modal image pairs and multi-spectral image pairs. The proposed method describes the neighbourhood of feature points combining frequency and spatial information using multi-scale and multi-oriented Log- Gabor filters. Experimental results show the validity of the proposed approach and also the improvements with respect to the state of the art. |
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IEEE |
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Quebec City, QC, Canada |
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English |
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2015 IEEE International Conference on Image Processing (ICIP) |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
40 |
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