Juan Carlos Valdiviezo-NCentro de Investigación en Ciencias de Información Geoespacial, México · Sede CdMx
Juan Carlos Valdiviezo-N
Ph.D. in Optical Sciences
Looking for a one-year research stay
About
51
Publications
10,321
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
323
Citations
Citations since 2017
Introduction
Juan Carlos Valdiviezo-N currently works at Centro de Investigación en Ciencias de la Información Geoespacial. Juan does research in Digital Image Processing and Remote Sensing Applications. Their current project is 'Urban monitoring.'
Additional affiliations
November 2013 - December 2013
January 2012 - present
January 2012 - August 2016
Publications
Publications (51)
Several built-up indices have been proposed in the literature in order to extract the urban sprawl from satellite data. Given their relative simplicity and easy implementation, such methods have been widely adopted for urban growth monitoring. Previous research has shown that built-up indices are sensitive to different factors related to image reso...
When recovering smooth phases by phase unwrapping algorithms, many non-iterative algorithms are available. However, normally those algorithms offer approximations of the current phase that cannot be accurate enough. This is because the majority of them are based on global approaches, instead of local ones. Although the smooth estimations are not of...
Many works have been implemented to describe how seismic vertical displacement maps can be generated from synthetic aperture radar (SAR) images. The theory that supports these works is a very interesting field in remote sensing which is called differential interferometric SAR (DInSAR). However, behind this theory, there are many limitations and amb...
Morphological processing has found several applications in image analysis and pattern recognition. Some of these techniques, known as morphological reconstruction algorithms, have been employed for land cover classification in remote sensing data. In this paper, we analyse the mathematical foundations, applications, and limitations of reconstructio...
The mistletoe Phoradendron velutinum (P. velutinum) is a pest that spreads rapidly and uncontrollably in Mexican forests, becoming a serious problem since it is a cause of the decline of 23.3 million hectares of conifers and broadleaves in the country. The lack of adequate phytosanitary control has negative social, economic, and environmental impac...
The two-dimensional phase unwrapping problem (PHUP) has been solved with discrete Fourier transforms (FTs) and many other techniques traditionally. Nevertheless, a formal way of solving the continuous Poisson equation for the PHUP, with the use of continuous FT and based on distribution theory, has not been reported yet, to our knowledge. The well-...
The continuous recording of images of the Earth’s surface through Earth observation satellites has enabled the study of large-scale dynamical process, such as urbanization. Mapping the urban land cover at a given time is a first-order problem that has been largely addressed, and for which several acceptable solutions exist. A second-order problem i...
Synthetic aperture radar (SAR) applications related to phase estimation, just as studies on subsidence, generation of digital elevation models or time series analyses of Earth surface changes, require an adequate phase unwrapping (PU) process. This process should imply at least a qualitative fringe analysis of certain small regions of the complete...
This research implements Genetic Programming to design a spectral index that allows the automated detection of the species Phoradendron Velutinum because it is a pest that leads to the detriment of forest health causing serious damage to the host trees. Employing multispectral aerial images taken in the field, pre-processed and selected for the cre...
Data supporting the manuscript entitled "Urban expansion and its impact on meteorological variables of the city of Merida, Mexico: discussion"
The monitoring of rivers based on remote sensing data provides an opportunity for
the observation of the natural dynamics of water and flood conditions. Taking advantage of the availability of radar data, we describe a methodology used to detect the river’s water surface flooding patterns and the size of floods using observations from Sentinel-1 im...
The monitoring of rivers based on remote sensing data provides an opportunity for the observation of the natural dynamics of water and flood conditions. Taking advantage of the availability of radar data, we describe a methodology used to detect the river's water surface flooding patterns and the size of floods using observations from Sentinel-1 im...
Recently, a theory on local polynomial approximations for phase-unwrapping algorithms, considering a state space analysis, has been proposed in Appl. Opt. 56, 29 (2017). Although this work is a suitable methodology to deal with relatively low signal to noise ratios observed in the wrapped phase, the methodology has been developed only for local-pol...
Several autofocus algorithms based on the analysis of image sharpness have been proposed for microscopy applications. Since autofocus functions (AFs) are computed from several images captured at different lens positions, these algorithms are considered computationally intensive. With the aim of presenting the capabilities of dedicated hardware to s...
Nowadays, remote sensing data taken from artificial satellites require high space communications bandwidths as well as high computational processing burdens due to the vertiginous development and specialisation of on-board payloads specifically designed for remote sensing purposes. Nevertheless, these factors become a severe problem when considerin...
Maya milpa is one of the most important agrifood systems in Mesoamerica, not only because its ancient origin but also due to lead an increase in landscape diversity and to be a relevant source of families food security and food sovereignty. Nowadays, satellite remote sensing data, as the multispectral images of Sentinel-2 platforms, permit us the m...
Water body classification is a topic of great interest, especially for the effective
management of floods. Synthetic aperture radar (SAR) imaging has demonstrated a great
potential for water monitoring, given its capacity to register images independent of weather conditions. Several algorithms for water detection using SAR images are based on optim...
En este artículo se realiza un análisis de la correlación entre el crecimiento de la mancha urbana y el cambio de temperaturas de la ciudad de Mérida, Yucatán, México, mediante la implementación de técnicas de inteligencia artificial enfocadas a la segmentación de imágenes. Partiendo de una secuencia multitemporal de imágenes satelitales registrada...
The retarded potential, a solution of the non-homogeneous wave equation, is a subject of particular interest in many physics and engineering applications. Examples of such applications may be the problem of solving the wave equation involved in the emission and reception of a signal in a synthetic aperture radar (SAR), scattering and backscattering...
This paper introduces an autonomous hybrid technique designed for the digital restoration of the missing parts and occluding artifacts in damaged historical or artistic color documents. For this purpose, a hyperspectral imaging device is used to acquire sets of images in the visible and near infrared ranges. Assuming the presence of linearly mixed...
We investigated the performance of DullRazor® to remove hairs from a phantom mimicking a skin pigmented lesion. Results indicates that DullRazor® performed relatively well only when the phantom was illuminated at the green and red wavelengths.
In this research the Hurst exponent H is used for quantifying the fractal features of LAN DSAT images. The Hurst exponent is estimated by means of the Detrending Moving Average (DMA), an algorithm based on a generalized high-dimensional variance around a moving average low-pass filter. Hence, for a two-dimensional signal, the algorithm first genera...
Melanoma is the most deadly form of skin cancer in human in all over the world with an increase number of victims yearly. One traditional form of diagnosis melanoma is by using the so called ABCDE rule which stands for Asymmetry, Border, Color, Diameter and Evolution of the lesion. For melanoma lesions, the color as a descriptor exhibits heterogene...
This research introduces an automatic technique designed for the digital restoration of the damaged parts in historical documents. For this purpose an imaging spectrometer is used to acquire a set of images in the wavelength interval from 400 to 1000 nm. Assuming the presence of linearly mixed spectral pixels registered from the multispectral image...
An artificial neural network model based on dendritic computation using two lattice metrics is introduced in this paper. A description of the mathematical framework of the proposed model is provided and its corresponding learning algorithm is presented in mathematical pseudocode. Computational experiments are given to demonstrate the effectiveness...
Autofocus is of fundamental importance for a real time automatic system. In many microscopy applications, a
desired automatic system should provide the best focused image with enough accuracy and the least computation
time. During the last years, several metrics based on images have been proposed for the autofocus process.
Although many of these te...
Multispectral imaging has motivated new applications related to quality monitoring for industrial applications due to its capability of analysis based on spectral signatures. In practice, however, a multispectral system used for such purposes is limited because of the large amount of data to be analyzed, being necessary to develop fast methods for...
This paper introduces a lattice algebra procedure that can be used for the multispectral analysis of historical documents and artworks. Assuming the presence of linearly mixed spectral pixels captured in a multispectral scene, the proposed method computes the scaled min- and max-lattice associative memories to determine the purest pixels that best...
These images are the ones used in Mateos-Pérez, J. M., Redondo, R., Nava, R., Valdiviezo, J. C., Cristóbal, G., Escalante-Ramírez, B., Ruiz-Serrano, M. J., Pascau J. and Desco, M. (2012), Comparative evaluation of autofocus algorithms for a real-time system for automatic detection of Mycobacterium tuberculosis. Cytometry Part A. doi: 10.1002/cyto.a...
We present a two layer dendritic hetero-associative memory that gives high percentages of correct classification for typical pattern recognition problems. The memory is a feedforward dendritic network based on lattice algebra operations and can be used with multivalued real inputs. A major consequence of this approach shows the inherent capability...
Multispectral imaging has given place to important applications related
to classification and identification of objects from a scene. Because of
multispectral instruments can be used to estimate the reflectance of
materials in the scene, these techniques constitute fundamental tools
for materials analysis and quality control. During the last years,...
Microscopy images must be acquired at the optimal focal plane for the objects of interest in a scene. Although manual focusing is a standard task for a trained observer, automatic systems often fail to properly find the focal plane under different microscope imaging modalities such as bright field microscopy or phase contrast microscopy. This artic...
An essential and indispensable component of automated microscopy framework is the automatic focusing system, which determines the in-focus position of a given field of view by searching the maximum value of a focusing function over a range of z-axis positions. The focus function and its computation time are crucial to the accuracy and efficiency of...
This manuscript describes a new technique for segmenting color images in different color spaces based on geometrical properties
of lattice auto-associative memories. Lattice associative memories are artificial neural networks able to store a finite set
X of n-dimensional vectors and recall them when a noisy or incomplete input vector is presented....
We present a two layer dendritic auto-associative memory with high rates of perfect recall of exemplar grayscale images distorted by different transformations or corrupted by random noise. The memory is a feedforward network based on dendritic computing employing lattice algebraic operations and is capable of dealing with real valued inputs. A majo...
An essential and indispensable component of automated microscopy is the automatic focusing system, which determines the in-focus position of a given field of view by searching for the maximal of an autofocus function over a range of z-axis positions. The autofocus function and its computation time are crucial to the accuracy and efficiency of the s...
We present a two layer dendritic auto-associative memory with high rates of perfect recall of exemplar grayscale images distorted by different transformations or corrupted by random noise. The memory is a feedforward network based on dendritic computing employing lattice algebraic operations and is capable of dealing with real valued inputs. A majo...
This paper describes a technique for segmenting color images in different color spaces based on lattice auto-associative memories.
Basically, the min- or max auto-associative memories can be used to determine tetrahedra enclosing different subsets of image
pixels. The column vectors of either memory, additively scaled, correspond to the most satura...
Recent developments, based on lattice auto-associative memories, have been proposed as novel and alternative techniques for endmember determination in hyperspectral imagery. The present paper discusses and compares three such methods using, as a case study, the generation of vegetation abundance maps by constrained linear unmixing. The first method...
Lattice associative memories also known as morphological associative memories are fully connected feedforward neural networks with no hidden layers, whose computation at each node is carried out with lattice algebra operations. These networks are a relatively recent development in the field of associative memories that has proven to be an alternati...
This manuscript introduces a new technique for autonomous segmentation of color images in Red-Green-Blue (RGB) space that makes use of lattice auto-associative memories (LAAMs). LAAMs are artificial neural networks able to store a finite set X of pattern vectors and retrieve them almost correctly when a noisy or incomplete input is presented. Two d...
Lattice independence and strong lattice independence of a set of pattern vectors are fundamental mathematical properties that lie at the core of pattern recognition applications based on lattice theory. Specifically, the development of morphological associative memories robust to inputs corrupted by random noise are based on strong lattice independ...
The advances in image spectroscopy have been applied for Earth observation at different wavelengths of the electromagnetic spectrum using aircrafts or satellite systems. This new technology, known as hyperspectral remote sensing, has found many applications in agriculture, mineral exploration and environmental monitoring since images acquired by th...
Projects
Projects (3)
ICASST 2022 is a scientific forum for the dissemination of basic research and/or technological development projects, which allows interaction between professionals, academics and industrialists, promoting scientific-technological collaborations in the aerospace field and related areas. The program includes oral and mural (poster)
presentations, keynote lectures given by widely recognized national and international experts in their area, as well as courses/workshops. The conference will be held in a hybrid way, face-to-face/virtual.
ICASST 2022 will be held at the facilities of Centro de Desarrollo Aeroespacial, Instituto Politécnico Nacional, in the historical center of Mexico City, Mexico. The face-to-face modality will take place as long as sanitary conditions allow it.
