Nelson Diaz

Pontificia Universidad Católica de Valparaíso | PUCV · School of Electrical Engineering

p>Multispectral Imaging (MSI) collects a datacube of spatio-spectral information of a scene. Many acquisition methods for spectral imaging use scanning, preventing its widespread usage for dynamic scenes. On the other hand, the conventional color filter array (CFA) method often used to sample color images has also been extended to snapshot MSI usin...

We propose a modification to the rolling shutter mechanism found in CMOS detectors by shuffling the pixels in every scanline. This potential hardware modification improves the sampling of the space-time datacube, allowing the recovery of high-speed videos from a single image using either tensor completion methods or reconstruction algorithms often...

Spectral image classification uses the huge amount of information provided by spectral images to identify objects in the scene of interest. In this sense, spectral images typically contain redundant information that is removed in later processing stages. To overcome this drawback, compressive spectral imaging (CSI) has emerged as an alternative acq...

Sensing a spectral image data cube has traditionally been a time-consuming task since it requires a scanning process. In contrast, compressive spectral imaging (CSI) has attracted widespread interest since it requires fewer samples than scanning systems to acquire the data cube, thus improving the sensing speed. CSI captures linear projections of t...

Imaging spectroscopy collects the spectral information of a scene by sensing all the spatial information across the electromagnetic wavelengths and are useful for applications in surveillance, agriculture, and medicine, etc. In contrast, compressive spectral imaging (CSI) systems capture compressed projections of the scene, which are then used to r...

Phase retrieval (PR) is a challenging problem with applications in various fields, ranging from microscopy to astronomy. Currently, novel computational imaging systems for PR exploit the modulation of the optical field through \acrfull{rcca} to recover the amplitude and phase from a distorted beam without prior knowledge, solving an ill-posed optim...

Phase retrieval (PR) is a challenging problem with applications in various fields, ranging from microscopy to astronomy. Currently, novel computational imaging systems for PR exploit the modulation of the optical field through \acrfull{rcca} to recover the amplitude and phase from a distorted beam without prior knowledge, solving an ill-posed optim...

We extended the 3D-Sphere Packing to design a Multiplexed Multispectral Filter Array that increases the measurement signal-to-noise ratio and allows an increase in the of number bands, approaching the resolutions expected for hyperspectral imaging systems.

This work presents a binary coded aperture (CA) design using sphere packing (SP) to determine the number of light entries in a compressive ultrafast photography (CUP) system. Our proposed approach leverages the uniform sensing that yields SP and the temporal shifting induced by the galvanometer to achieve uniform sensing.

This chapter provides a comprehensive and up-to-date review of the rolling shutter (RS) mechanism found in complementary metal-oxide semiconductor (CMOS) imaging sensors as a coding opportunity for high-speed videos. Based on this, we present a cutting-edge readout architecture called shuffled rolling shutter (SRS) that optimally designs the scanli...

Multispectral imaging (MSI) collects a datacube of spatio-spectral information of a scene. Many acquisition methods for spectral imaging use scanning, preventing its widespread usage for dynamic scenes. On the other hand, the conventional color filter array (CFA) method often used to sample color images has also been extended to snapshot MSI using...

We propose a method to design a multiplexed Multispectral Filter Array (MSFA) based on Optimal Sphere Packing (OSP) in a 4D-Euclidean space that promotes uniformity and improved signal-to-noise ratio in the measurement process of the 3D-datacube while delivering enhanced reconstructions.

This work presents a mathematical framework to design 4D-coded aperture (CA)s for compressive snapshot spectral video (SV) exploiting 4D-sphere packing (SP). Simulation results using state-of-the-art datasets and metrics show a promising performance of the proposed approach to capture high-dimensional datacubes with limited sensing resources.

Multispectral Imaging (MSI) collects a datacube of spatio-spectral information of a scene. Many acquisition methods for spectral imaging use scanning, preventing its widespread usage for dynamic scenes. On the other hand, the conventional color filter array (CFA) method often used to sample color images has also been extended to snapshot MSI using...

We propose an optimal distribution of spectral filters in a multispectral filter array based on packing congruent spheres in a 3D-euclidean space, promoting uniformity in the sensing of the 3D-datacube while leading to improved reconstructions.

3D modeling based on point clouds requires ground-filtering algorithms that separate ground from non-ground objects. This study presents two ground filtering algorithms. The first one is based on normal vectors. It has two variants depending on the procedure to compute the k-nearest neighbors. The second algorithm is based on transforming the cloud...

3D modeling based on point clouds requires ground-filtering algorithms that separate ground from non-ground objects. This study presents two ground filtering algorithms. The first one is based on normal vectors. It has two variants depending on the procedure to compute the k-nearest neighbors. The second algorithm is based on transforming the cloud...

Spectral image classification uses the huge amount of information provided by spectral images to identify objects in the scene of interest. In this sense, spectral images typically contain redundant information that is removed in later processing stages. To overcome this drawback, compressive spectral imaging (CSI) has emerged as an alternative acq...

Spectral image classification uses the huge amount of information provided by spectral images to identify objects in the scene of interest. In this sense, spectral images typically contain redundant information that is removed in later processing stages. To overcome this drawback, compressive spectral imaging (CSI) has emerged as an alternative acq...

We propose a slight modification to the rolling shutter by shuffling the scanline mechanism to significantly improve its sampling ability to recover high speed videos from a single image using compressive reconstruction algorithms.

In this research, we used bio-inspired metaheuristics, as artificial immune systems and ant colony algorithms that are based on a number of characteristics and behaviors of living things that are interesting in the computer science area. This paper presents an evaluation of bio-inspired solutions to combinatorial optimization problem, called the Jo...

In this research we used bio-inspired metaheuristics, as artificial immune systems and ant colony algorithms that are based on a number of characteristics and behaviors of living things that are interesting in the computer science area. This paper presents an evaluation of bio-inspired solutions to combinatorial optimization problem, called the Job...

This work introduces a light field architecture aimed at simultaneously performing multi-spectral compressive imaging and light field acquisition in a single-sensor device. The proposed architecture exploits a microlens array combined with coded aperture patterns.

This paper presents a gradient thresholding algorithm (GTA) to adaptively compute the subsequent colored coded apertures to be used in a compressive spectral imaging sensor yielding to a reconstructed spectral datacube with high image quality.

Imaging spectroscopy is an important area with many applications in surveillance, agriculture and medicine. The disadvantage of conventional spectroscopy techniques is that they collect the whole datacube. In contrast, compressive spectral imaging systems capture snapshot compressive projections, which are the input of reconstruction algorithms to...

The coded aperture snapshot spectral imaging system (CASSI) is an imaging architecture which senses the three dimensional informa-tion of a scene with two dimensional (2D) focal plane array (FPA) coded projection measurements. A reconstruction algorithm takes advantage of the compressive measurements sparsity to recover the underlying 3D data cube....

Compressive hyperspectral imaging systems (CSI) capture the three-dimensional (3D) information of a scene by measuring two dimensional (2D) using a small set of coded focal plane array (FPA) compressive measurement. A reconstruction algorithm takes advantage of the compressive measurements sparsity to recover the 3D data cube. Traditionally, CASSI...

En el presente artículo se establece una implementación de un algoritmo inmune artificial conocido como CLONALG para dar solución al problema de Job shop Scheduling (JSP), este es un problema de gran interés para la industria. Una de sus principales características es su naturaleza combinatoria y su complejidad, NP-Hard, la cual implica altos costo...

En el presente artículo se establece una implementación de un algoritmo inmune artificial conocido como CLONALG para dar solución al problema de Job shop Scheduling (JSP), este es un problema de gran interés para la industria. Una de sus principales características es su naturaleza combinatoria y su complejidad, NP-Hard, la cual implica altos costo...