Sebastian Lopez

Sebastian Lopez
Universidad de Las Palmas de Gran Canaria | ULPGC · Instituto Universitario de Microelectrónica Aplicada (IUMA)

PhD

About

145
Publications
18,210
Reads
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1,396
Citations
Citations since 2017
41 Research Items
873 Citations
2017201820192020202120222023050100150
2017201820192020202120222023050100150
2017201820192020202120222023050100150
2017201820192020202120222023050100150
Additional affiliations
January 2002 - present
Universidad de Las Palmas de Gran Canaria
January 2002 - present
Universidad de Las Palmas de Gran Canaria
Position
  • Professor (Associate)

Publications

Publications (145)
Article
Full-text available
Hyperspectral Imaging (HSI) techniques have demonstrated potential to provide useful information in a broad set of applications in different domains, from precision agriculture to environmental science. A first step in the preparation of the algorithms to be employed outdoors starts at a laboratory level, capturing a high amount of samples to be an...
Article
Full-text available
The integration of video sensors on-board satellites is becoming a trend in the space industry, since they provide extra information in the temporal domain when compared with traditional remote sensing imaging acquisition equipment. The inclusion of the temporal dimension together with the constant increase in the sensor resolution supposes a chall...
Article
Full-text available
Onboard data processing for on-the-fly decision-making applications has recently gained momentum in the field of remote sensing. In this context, hyperspectral anomaly detection has received special attention since its main purpose lies in the identification of abnormal events in an unsupervised manner. Nevertheless, onboard real-time hyperspectral...
Article
Full-text available
Over the last years, convolutional neural networks (CNNs) have been widely used in remote sensing applications, such as marine surveillance, traffic management, or road networks detection. However, since CNNs have extremely high computational, bandwith, and memory requirements, the hardware implementation of a CNN on space-grade devices like field-...
Article
The lossy compressor algorithm for hyperspectral image systems (HyperLCA) compressor is a transform-based algorithm specifically designed for the real-time compression of hyperspectral images captured by pushbroom scanners, using limited computational resources. It is based on the HyperLCA transform, which follows an unmixinglike strategy to indepe...
Article
Full-text available
The use of next-generation and high-resolution imaging sensors is gaining interest for space missions, because of their properties for identification and exploration purposes. It is expected that the demand of video sensors in the space industry will increase during the next years, mainly for monitorization and exploration missions. In this context...
Article
Full-text available
Hyperspectral sensors that are mounted in unmanned aerial vehicles (UAVs) offer many benefits for different remote sensing applications by combining the capacity of acquiring a high amount of information that allows for distinguishing or identifying different materials, and the flexibility of the UAVs for planning different kind of flying missions....
Article
Full-text available
Remote-sensing platforms, such as Unmanned Aerial Vehicles, are characterized by limited power budget and low-bandwidth downlinks. Therefore, handling hyperspectral data in this context can jeopardize the operational time of the system. FPGAs have been traditionally regarded as the most power-efficient computing platforms. However, there is little...
Article
Full-text available
Multispectral imaging (MI) techniques are being used very often to identify different properties of nature in several domains, going from precision agriculture to environmental studies, not to mention quality inspection of pharmaceutical production, art restoration, biochemistry, forensic sciences or geology, just to name some. Different implementa...
Article
Full-text available
This paper describes a novel hardware implementation of a lossy multispectral and hyperspectral image compressor for on-board operation in space missions. The compression algorithm is a lossy extension of the Consultative Committee for Space Data Systems (CCSDS) 123.0-B-1 lossless standard that includes a bit-rate control stage, which in turn manag...
Article
Full-text available
The on-board processing of remotely sensed hyperspectral images is gaining momentum for applications that demand a quick response as an alternative to conventional approaches where the acquired images are off-line processed once they have been transmitted to the ground segment. However, the adoption of this on-board processing strategy brings furth...
Preprint
Full-text available
Most practical hyperspectral anomaly detection (AD) applications require real-time processing for detecting complex targets from their background. This is especially critical in defense and surveillance domains, but also in many other scenarios in which a rapid response is mandatory to save human lives. Dealing with such a high dimensionality of da...
Article
Full-text available
Remotely sensed hyperspectral imaging is a very active research area, with numerous contributions in the recent scientific literature. The analysis of these images represents an extremely complex procedure from a computational point of view, mainly due to the high dimensionality of the data and the inherent complexity of the state-of-the-art algori...
Conference Paper
Full-text available
Hyperspectral sensors are able to provide information that is useful for many different applications. However, the huge amounts of data collected by these sensors are not exempt of drawbacks, especially in remote sensing environments where the hyperspectral images are collected on-board satellites and need to be transferred to the Earths surface. I...
Article
Full-text available
Currently, the use of hyperspectral imaging (HSI) for the inspection of microscopic samples is an emerging trend in different fields. The use of push-broom hyperspectral (HS) cameras against other HSI technologies is motivated by their high spectral resolution and their capabilities to exploit spectral ranges beyond 1000 nm. Nevertheless, using pus...
Article
Full-text available
The utilization of hyperspectral imaging sensors has gained a significant relevance among many different applications due to their capability for collecting a huge amount of information across the electromagnetic spectrum. These sensors have been traditionally mounted on-board satellites and airplanes in order to extract information from the Earth’...
Article
In recent years, anomaly detection (AD) has enjoyed a growing interest in hyperspectral data analysis. However, most state-of-the-art detectors need to work with the entire hyperspectral cube, what prevents their use for applications under real-time constraints, especially when the hyperspectral data are collected by push-broom scanners that acquir...
Article
The increment in the data rate of the new-generation hyperspectral sensors is making more critical the necessity of lossy compression solutions able to achieve higher compression ratios (CRs). In this paper, a transform-based lossy compressor, namely lossy compression algorithm for hyperspectral image systems (HW-HyperLCA), is proposed as a modific...
Article
Most practical hyperspectral anomaly detection (AD) applications require real-time processing for detecting complex targets from their background. This is especially critical in defense and surveillance domains, but also in many other scenarios, in which a rapid response is mandatory to save human lives. Dealing with such a high dimensionality of d...
Article
Real-time hyperspectral imaging on-board compression represents a critical processing step in many remote sensing applications where the acquired hyperspectral data need to be efficiently stored and/or transferred. However, the complexity of the compression algorithms as well as the volume of data to be compressed and the limited computational reso...
Conference Paper
Full-text available
Anomaly detection is an increasingly important task when dealing with hyperspectral images in order to distinguish rare objects whose spectral characteristics substantially deviates from those of the neighboring materials. In this paper, a novel technique for accurate detection of anomalies in hyperspectral images is introduced. One of the main fea...
Article
Full-text available
Interest on anomaly detection for hyperspectral images has increasingly grown during the last decades due to the diversity of applications that benefit from this technique. However, the high computational cost inherent to this detection procedure seriously limits its processing efficiency, especially for onboard application scenarios. In this paper...
Article
Full-text available
Application-oriented solutions based on the combination of different technologies such as unmanned aerial vehicles (UAVs), advanced sensors, precise GPS and embedded devices have led to important improvements in the field of cyber-physical systems. Agriculture, due to its economic and social impact on the global population, which is expected to rea...
Article
Full-text available
Space missions are facing disruptive innovation since the appearance of small, lightweight, and low-cost satellites (e.g., CubeSats). The use of commercial devices and their limitations in cost usually entail a decrease in available on-board computing power. To face this change, the on-board processing paradigm is advancing towards the clustering o...
Conference Paper
Full-text available
In this paper, a Field Programmable Gate Array (FPGA) implementation of the CCSDS 123.0-B-1 Lossless Multispec-tral and Hyperspectral Image Compression Algorithm is presented. This recommended standard provides a tradeoff between compression performance and computational complexity , which makes it suitable for onboard applications. A High-Level Sy...
Article
Full-text available
Dimensionality reduction represents a critical preprocessing step in order to increase the efficiency and the performance of many hyperspectral imaging algorithms. However, dimensionality reduction algorithms, such as the Principal Component Analysis (PCA), suffer fromtheir computationally demanding nature, becoming advisable for their implementati...
Conference Paper
Full-text available
ENABLE-S3 is a use-case driven European research project focusing on the implementation and validation of autonomous cyber-physical systems (CPS) in different application domains. This work describes the efforts done so far in the development of infrastructure and tools to make improved validation concepts in agriculture, being part of one of the t...
Article
Full-text available
Hyperspectral sensors are able to provide information that is useful for many different applications. However, the huge amounts of data collected by these sensors are not exempt of drawbacks, especially in remote sensing environments where the hyperspectral images are collected on-board satellites and need to be transferred to the earth’s surface....
Article
Full-text available
Anomaly detection (AD) is an important technique in hyperspectral data analysis that permits to distinguish rare objects with unknown spectral signatures that are particularly not abundant in a scene. In this paper, a novel algorithm for an accurate detection of anomalies in hyperspectral images with a low computational complexity, named ADALOC², i...
Article
Hyperspectral imaging systems are a powerful tool for obtaining surface information in many different spectral channels that can be used in many different applications. Nevertheless, the huge amount of information provided by hyperspectral images also has a downside, since it has to be processed and analyzed. For such purpose, parallel hardware dev...
Article
This paper presents a study of the parallelism of a Principal Component Analysis (PCA) algorithm and its adaptation to a manycore MPPA (Massively Parallel Processor Array) architecture, which gathers 256 cores distributed among 16 clusters. This study focuses on porting hyperspectral image processing into manycore platforms by optimizing their proc...
Article
Linear spectral unmixing is one of the nowadays hottest research topics within the hyperspectral imaging community, being a proof of this fact the vast amount of papers that can be found in the scientific literature about this challenging task. A subset of these works is devoted to the acceleration of previously published unmixing algorithms for ap...
Article
Remote sensing systems equipped with multispectral and hyperspectral sensors are able to capture images of the surface of the Earth at different wavelengths. In these systems, hyperspectral sensors typically provide images with a high spectral resolution but a reduced spatial resolution, while on the contrary, multispectral sensors are able to prod...
Conference Paper
Full-text available
Hyperspectral Imaging is an emerging technology for medical diagnosis issues due to the fact that it is a non-contact, non-ionizing and non-invasive sensing technique. The work presented in this paper tries to establish a novel way in the use of hyperspectral images to help neurosurgeons to accurately determine the tumour boundaries in the process...
Article
Linear spectral unmixing is nowadays an essential tool to analyze remotely sensed hyperspectral images. Although many different contributions have been uncovered during the last two decades, the majority of them are based on dividing the whole process of linearly unmixing a given hyperspectral image into three sequential steps: 1) estimation of the...
Conference Paper
Full-text available
Hyperspectral imaging is an active research field for remote sensing applications. These images provide a lot of information about the characteristics of the materials due to the high spectral resolution. This work is focused in the use of this kind of information to detect tumour tissue, particularly brain cancer tissue. In recent years, the study...
Conference Paper
One of the first problems that a hardware designer needs to solve when facing a new and complex electronic design, is to know in advance where the critical parts of the design are, and how many resources the design will require. This information will ease the developing of feasible systems and will help in the design of well suited architectures. T...
Conference Paper
Linear unmixing of hyperspectral images has rapidly become one of the most widely utilized tools for analyzing the content of hyperspectral images captured by state-of-the-art remote hyperspectral sensors. The aforementioned unmixing process consists of the following three sequential steps: dimensionality estimation, endmember extraction and abunda...
Article
Spectral unmixing is an important task for remotely sensed hyperspectral data exploitation. It amounts the identification of pure spectral signatures (endmembers) in the data, and the estimation of the abundance of each endmember in each (possibly mixed) pixel. A challenging problem in spectral unmixing is how to determine the number of endmembers...
Article
Full-text available
The papers in this special section focus on the technology and applications supported by hyperspectral imaging and signal processing.
Conference Paper
It is highly desirable to know in advance the transaction of data in the design of any electronic embedded system. It is of especial interest for data-intensive applications, such as complex video systems, when the options available in the video decoder continuously change and/or the features of the input video sequences are different. This paper e...
Article
Full-text available
Surface roughness is an important factor in bare soil microwave radiation for the observation of the Earth. Correlation length and standard deviation of surface height are the two statistical parameters that describe surface roughness. However, when the number of data points is large, the calculation of surface roughness parameters becomes time-con...
Article
A challenging problem in spectral unmixing is how to determine the number of endmembers in a given scene. One of the most popular ways to determine the number of endmembers is by estimating the virtual dimensionality (VD) of the hyperspectral image using the well-known Harsanyi–Farrand–Chang (HFC) method. Due to the complexity and high dimensionali...
Article
The increase of data rates and data volumes in present remote sensing payload instruments, together with the restrictions imposed in the downlink connection requirements, represent at the same time a challenge and a must in the field of data and image compression. This is especially true for the case of hyperspectral images, in which both, reductio...
Conference Paper
Endmember extraction and abundances calculation represent critical steps within the process of linearly unmixing a given hyperspectral image because of two main reasons. The first one is due to the need of computing a set of accurate endmembers in order to further obtain confident abundance maps. The second one refers to the huge amount of operatio...
Article
Hyperspectral imaging instruments capture and collect hundreds of different wavelength data corresponding to the same surface. As a result, tons of information must be stored, processed and transmitted to ground. However, the downlink bandwidth is limited, and transmitting all data from the satellite to ground is a slow task that jeopardizes the us...
Article
Earth observation hyperspectral imaging instruments capture and collect hundreds of different wavelength data corresponding to the same surface. As a result, tons of information must be stored, processed, and transmitted to ground by means of a combination of time-consuming processes. However, one of the requirements of paramount importance when de...
Article
Hyperspectral imaging represents the state-of-theart technique in those applications related to environmental monitoring, military surveillance, or rare mineral detection. However, one of the requirements of paramount importance when dealing with such scenarios is the ability to achieve real-time constraints taking into account the huge amount of d...
Conference Paper
Efficient onboard satellite hyperspectral image compression represents a necessity and a challenge for current and future space missions. Therefore, it is mandatory to provide hardware implementations for this type of algorithms in order to achieve the constraints required for onboard compression. In this work, we implement the Lossy Compression fo...
Conference Paper
This paper presents a new method in order to perform the endmembers extraction with the same accuracy in the results that the well known Winter’s N-Finder algorithm but with less computational effort. In particular, our proposal makes use of the Orthogonal Subspace Projection algorithm, OSP, as well as the information provided by the dimensionality...
Article
Hyperspectral image processing represents a valuable tool for remote sensing of the Earth. This fact has led to the inclusion of hyperspectral sensors in different airborne and satellite missions for Earth observation. However, one of the main drawbacks encountered when dealing with hyperspectral images is the huge amount of data to be processed, i...
Conference Paper
FPGA-based embedded systems are gaining relevance for implementing a wide range of applications. Part of their success is due to their balanced compromise between performance and flexibility, but also because of their capability for exploiting the dynamic reconfiguration. However, the costly reconfiguration process and the lack of management suppor...
Article
The deblocking filter (DF) is one of the most complex functional cores of the H.264/AVC and SVC codecs. Its computational cost is heavily dependent on the video profile and the selected scalability level. With the goal of providing faster and better solutions, developers are focused on designing hardware architectures. Thus, it is possible taking a...
Article
One of the main problems in the analysis of remotely sensed hyperspectral data cubes is the presence of mixed pixels, which arise when the spatial resolution of the sensor is not able to separate spectrally distinct materials. Due to this reason, spectral unmixing has become one of the most important tasks for hyperspectral data exploitation. Howev...