Monochromatic Channels Research Articles

Space-Time-Color (STC) Scheme With Symbol-Hopping for Color Shift Keying (CSK) Modulation

This letter proposes a novel coding scheme for Visible Light Communications (VLC) systems using symbol mapping permutations on the color domain. The permutation is done through symbol-hopping over the points of an optimized 4-CSK constellation. This scheme provides diversity gains, promises robustness against monochromatic channel degradation, and increases the information security of the communication link. It can also be used in conjunction with Single-Input and Single-Output (SISO) systems, as well as in Multiple-Input and Multiple-Output (MIMO) systems. Monte Carlo computational simulations evaluate the performance of the proposed scheme over the conventional QuadLED (QLED) CSK system and other codes, showing superior coding and diversity gains over two direct competitors, under a Rician flat-fading channel.

Pixel-Based Image Processing for CIE Standard Sky Classification through ANN

Digital sky images are studied for the definition of sky conditions in accordance with the CIE Standard General Sky Guide. Likewise, adequate image-processing methods are analyzed that highlight key image information, prior to the application of Artificial Neural Network classification algorithms. Twenty-two image-processing methods are reviewed and applied to a broad and unbiased dataset of 1500 sky images recorded in Burgos, Spain, over an extensive experimental campaign. The dataset comprises one hundred images of each CIE standard sky type, previously classified from simultaneous sky scanner data. Color spaces, spectral features, and texture filters image-processing methods are applied. While the use of the traditional RGB color space for image-processing yielded good results (ANN accuracy equal to 86.6%), other color spaces, such as Hue Saturation Value (HSV), which may be more appropriate, increased the accuracy of their global classifications. The use of either the green or the blue monochromatic channels improved sky classification, both for the fifteen CIE standard sky types and for simpler classification into clear, partial, and overcast conditions. The main conclusion was that specific image-processing methods could improve ANN-algorithm accuracy, depending on the image information required for the classification problem.

Massively parallel neural circuits for stereoscopic color vision: Encoding, decoding and identification

Past work demonstrated how monochromatic visual stimuli could be faithfully encoded and decoded under Nyquist-type rate conditions. Color visual stimuli were then traditionally encoded and decoded in multiple separate monochromatic channels. The brain, however, appears to mix information about color channels at the earliest stages of the visual system, including the retina itself. If information about color is mixed and encoded by a common pool of neurons, how can colors be demixed and perceived?We present Color Video Time Encoding Machines (Color Video TEMs) for encoding color visual stimuli that take into account a variety of color representations within a single neural circuit. We then derive a Color Video Time Decoding Machine (Color Video TDM) algorithm for color demixing and reconstruction of color visual scenes from spikes produced by a population of visual neurons. In addition, we formulate Color Video Channel Identification Machines (Color Video CIMs) for functionally identifying color visual processing performed by a spiking neural circuit.Furthermore, we derive a duality between TDMs and CIMs that unifies the two and leads to a general theory of neural information representation for stereoscopic color vision. We provide examples demonstrating that a massively parallel color visual neural circuit can be first identified with arbitrary precision and its spike trains can be subsequently used to reconstruct the encoded stimuli. We argue that evaluation of the functional identification methodology can be effectively and intuitively performed in the stimulus space. In this space, a signal reconstructed from spike trains generated by the identified neural circuit can be compared to the original stimulus.

Image Encryption An Intelligent Approach of Color Visual Cryptography

Visual cryptography is a secret sharing method that uses human eyes to decrypt the secret. It has computation-free decoding process to decrypt the images. Generally visual cryptographic methods utilize the technique of secret sharing in which secret image is divided into shares and when k shares out of n stack together the secret image will reveal. In this paper we proposed a method of visual cryptography for colored images. We are using RGB color model for color images. First of all, image is divided into monochromatic channels then converts each individual image to binary image. After this we can apply basic VCS scheme. The secret image can be recovered by stacking share images. We are using Matlab7.4 for implementing our scheme.

Physiologic Responses to Stress and Changes in Atlantic Bluefin Tuna (T. thynnus) Meat Color During Trap Fisheries Capture and Processing in Sardinia (W. Mediterranean)

This study investigated plasma cortisol, lactate, and glucose as descriptors of hematological stressors; while the RGB color model using the percentage of monochromatic channels Red (Rp), Green (Gp), and Blue (Bp) was used for the analysis of muscular tissue of the Atlantic bluefin tuna, Thunnus thynnus. The experimental design provided a comparison of stressors and color channels Before and After the stress state and the analysis of variability of monochromatic channels for Fresh and Frozen specimens collected at three time intervals. Results showed a rapid accumulation of cortisol levels (from 73.3 ± 9.5 to 148.0 ± 21.2 ng/mL), lactate (from 5.7 ± 2.9 to 17.0 ± 2.2 μmol/mL), and glucose (from 83.5 ± 8.0 to 128.6 ± 19.3 mg/dL; p < 0.05). The colorimetric analysis highlighted that this accumulation did not in fact affect the color variability of muscle. Analysis of variance carried out to test the effects of color variability in Fresh samples showed significant differences for Rp, Gp, and Bp channels (p < 0.05), whereas no differences were found in Frozen samples. Highly significant differences (p < 0.001) were found comparing Fresh and Frozen for Rp and Bp, indicating a drop of these channels under diverse treatments.

Nonlinear pattern recognition correlators based on color-encoding single-channel systems.

In color pattern recognition, color channels are normally processed separately and afterward the correlation outputs are combined. This is the definition of multichannel processing. We combine a single-channel method with nonlinear filtering based on nonlinear correlations. These nonlinear correlations yield better discrimination than common matched filtering. The method codes color information as amplitude and phase distributions and is followed by correlations related to binary decompositions. The technique is based on binary decompositions of the red, green, and blue and the hue, saturation, and intensity monochromatic channels of the reference and of the input scene, after which the binary information on the red, green, and blue channels and that of the hue, saturation, and intensity channels are encoded as different angles of a phase distribution. We have applied the method to images degraded by high levels of substitutive noise. Results show that the sliced orthogonal nonlinear generalized correlation detects the target with a high degree of discrimination when other methods fail.

Multichannel colour pattern recognition using a minimum average correlation energy filter

A minimum average correlation energy filter is proposed for colour pattern recognition. The filter is designed to provide a delta-like correlation peak for the transmittance of the target when illuminated with several wavelengths, while minimizing the whole correlation plane energy. Thus, the filter can be used simultaneously in several monochromatic channels. The resulting correlation planes are blended using a simple pointwise technique providing a single final output plane with a very high discrimination. Computer simulations are presented.

Planetary Fourier spectrometer: An interferometer for atmospheric studies on board Mars 94 mission

PFS is a two-channel Fourier spectrometer operating in the infra-red wavelengths between 1.25 and 45 μm. The instrument will be used mainly in the study of the Martian atmosphere. The principal goals are the measurements of the atmospheric temperature and pressure, atmospheric constituents, aerosol and clouds, ground pressure for surface topography, optical and thermophysics properties of the Martian soil. PFS will fly on the Mars 94 spacecraft which should be launched in 1994 and reach the planet in 1995. It is essentially constituted by two different interferometers located in the same box which is divided into two parts. A dichroic placed on the PFS entrance is used to separate the spectral range into two parts, a division needed by the different optical materials which have to be used in each spectral range. The optical layout of the experiment is very compact. Each channel uses two cubic mirrors mounted on an L-structure pivoted on a motor. The motor moves the mechanics and permits the optical-path difference between the arms to be varied. Each interformeter operates in a different spectral range, respectively, between (1.25÷4.8) μm (8000÷2083cm−1) and (6÷45)μm (1666÷220)cm−1). The spectral resolution is 2 cm−1. The entrance aperture area is 30 cm2 per channel and the field of view is 2 and 4 degrees. Every measurement lasts about 4 s. The time and, therefore, the relative optical-path difference for the measurement of every point of the interferogram is given by the zero crossings of the interferogram of a reference monochromatic channel at 1.2 μm which uses a laser diode as source. The two interferograms are double-sided and will have 16384 and 4096 points, respectively, corresponding to spectra of 6250 and 1823 useful points.