Search results for "RGB"
showing 10 items of 116 documents
Maximum likelihood difference scaling of image quality in compression-degraded images.
2007
International audience; Lossy image compression techniques allow arbitrarily high compression rates but at the price of poor image quality. We applied maximum likelihood difference scaling to evaluate image quality of nine images, each compressed via vector quantization to ten different levels, within two different color spaces, RGB and CIE 1976 L(*)a(*)b(*). In L(*)a(*)b(*) space, images could be compressed on average by 32% more than in RGB space, with little additional loss in quality. Further compression led to marked perceptual changes. Our approach permits a rapid, direct measurement of the consequences of image compression for human observers.
High-end colorimetric display characterization using an adaptive training set
2011
A new, accurate, and technology-independent display color-characterization model is introduced. It is based on polyharmonic spline interpolation and on an optimized adaptive training data set. The establishment of this model is fully automatic and requires only a few minutes, making it efficient in a practical situation. The experimental results are very good for both the forward and inverse models. Typically, the proposed model yields an average model prediction error of about 1 ∆Eab* unit or below for several displays. The maximum error is shown to be low as well. freedom given to the model considering the choice of a tar- get color space and of the kernel and smoothing factor for the int…
Parameter-free adaptive step-size multiobjective optimization applied to remote photoplethysmography
2018
International audience; In this work, we propose to reformulate the objective function of Independent Component Analysis (ICA) to make it a better posed problem in the context of Remote photoplethysmography (rPPG). In recent previous works, linear combination coefficients of RGB channels are estimated maximizing the non-Gaussianity of ICA output components. However, in the context of rPPG a priori knowledge of the pulse signal can be incorporated into the component extraction algorithm. To this end, the contrast function of regular ICA is extended with a measure of periodicity formulated using autocorrelation. This novel semi-blind source extraction method for measuring rPPG has the interes…
Incorporating depth information into few-shot semantic segmentation
2021
International audience; Few-shot segmentation presents a significant challengefor semantic scene understanding under limited supervision.Namely, this task targets at generalizing the segmentationability of the model to new categories given a few samples.In order to obtain complete scene information, we extend theRGB-centric methods to take advantage of complementary depthinformation. In this paper, we propose a two-stream deep neuralnetwork based on metric learning. Our method, known as RDNet,learns class-specific prototype representations within RGB anddepth embedding spaces, respectively. The learned prototypesprovide effective semantic guidance on the corresponding RGBand depth query ima…
Capteurs et images aériennes pour l’évaluation du peuplement de mauvaises herbes
2013
AIRINOV is specialized in use of UAV for precision agriculture. Thanks to a high spatial resolution up to 1.5 cm/pixel in RGB images, discrimination between vegetation (crop row, weed) and soil can be done. Variability can be detected in weed density inside the whole field. The detection of weeds in the inter-row of hoed row crops was tested on RGB images. The methodology developed is based on Hough transform, and is composed of three main steps: image segmentation, soil/vegetation discrimination and crop rows localization. First results are promising but need complementary measures for validation.
Robustness of texture parameters for color texture analysis
2006
This article proposes to deal with noisy and variable size color textures. It also proposes to deal with quantization methods and to see how such methods change final results. The method we use to analyze the robustness of the textures consists of an auto-classification of modified textures. Texture parameters are computed for a set of original texture samples and stored into a database. Such a database is created for each quantization method. Textures from the set of original samples are then modified, eventually quantized and classified according to classes determined from a precomputed database. A classification is considered incorrect if the original texture is not retrieved. This metho…
<title>Stereoacuity determination at changing contrast of colored stereostimuli</title>
2003
Studies are focused on design and appraisal of an objective test for assessment of the stereovision quality in unfavorable conditions. Stereostimuli of different colors are used while the contrast of one of the stimulus being varied. Tests are based on principles of black-and-white and two primary color random dot stereotests. Experiments are divided by the method of stimuli display and separation: 1) stereoeffect is obtained haploscopically - by use of spectacles with color filters (blue and red) or prisms, 2) stimuli separation is obtained by liquid crystal shutters when both eye stimuli are demonstrated with a different delay. The stereovision threshold is determiend at different stimuli…
Characterization of a digital camera as an absolute tristimulus colorimeter
2003
An algorithm is proposed for the spectral and colorimetric characterization of digital still cameras (DSC) which allows them to be used as tele-colorimeters with CIE-XYZ color output, in cd/m2. The spectral characterization consists in the calculation of the color-matching functions from the previously measured spectral sensitivities. The colorimetric characterization consists in trans- forming the raw RGB digital data into absolute tristimulus values CIE-XYZ (in cd/m2) under variable and unknown spectroradiometric conditions. Thus, in the first stage, a gray balance was applied over the raw RGB digital data to convert them into RGB relative colorimetric values. In the second stage, an algo…
Shared feature representations of LiDAR and optical images: Trading sparsity for semantic discrimination
2015
This paper studies the level of complementary information conveyed by extremely high resolution LiDAR and optical images. We pursue this goal following an indirect approach via unsupervised spatial-spectral feature extraction. We used a recently presented unsupervised convolutional neural network trained to enforce both population and lifetime spar-sity in the feature representation. We derived independent and joint feature representations, and analyzed the sparsity scores and the discriminative power. Interestingly, the obtained results revealed that the RGB+LiDAR representation is no longer sparse, and the derived basis functions merge color and elevation yielding a set of more expressive…
Agar-based phantoms for skin diagnostic imaging
2020
Agar-based skin phantoms with different thicknesses and hemoglobin concentration were evaluated for diagnostics of skin lesions by RGB imaging. Scattering properties of the phantoms were simulated using intralipid, absorption properties – using lyophilized powder of human hemoglobin. RGB images of phantoms were captured by self-developed laboratory made devices. The algorithm for calculation of chromophore concentrations are based on Beer-Lambert law and includes the photon path length evaluated from the measured photon-time-of-flight signals. Optical properties and chromophore concentration maps of phantoms obtained from RGB images were analyzed. The influence of chromophore concentration …