Differential physiological response to heat and cold stress of tomato plants and its implication on fruit quality.

The upcoming climate change presents a great challenge for plant growth and development being extremes temperatures among the major environmental limitations to crop productivity. Understanding the repercussions of these extreme temperatures is of high importance to elaborate future strategies to confront crop damages. Tomato plants (Solanum lycopersicum L.) are one of the most cultivated crops and their fruits are consumed worldwide standing out for their organoleptic characteristics and nutritional value. Tomato plants are sensitive to temperatures below 12 °C and above 32 °C. In this study, Micro-Tom cultivar was used to evaluate the effects of extreme temperatures on the plant of tomato and the fruit productivity and quality from the stressed plants, either exposed to cold (4 °C for three nights per week) or heat (32 °C during the day, seven days per week) treatments. Total productivity and the percentage of ripe fruits per plant were evaluated together with foliar stress markers and the contents of photosynthetic pigments and tocochromanols. Fruit quality was also assessed determining lycopene contents, total soluble solids, total acidity and ascorbate contents. High temperatures altered multiple physiological parameters indicating a moderate stress, particularly decreasing fruit yield. As a response to this stress, plants enhanced their antioxidant contents both at leaf and fruit level. Low temperatures did not negatively affect the physiology of plants with similar yields as compared to controls, suggesting chilling acclimation. Both high and low temperatures, but most particularly the former, increased total soluble solids contents indicating that temperature control may be used as a strategy to modulate fruit quality.

A Dual Role for Abscisic Acid Integrating the Cold Stress Response at the Whole-Plant Level in Iris pseudacorus L. Growing in a Natural Wetland.

Leaf senescence, the last stage of the developmental program of leaves, can be induced by both internal and external signals. Cold stress-induced leaf senescence is an efficient strategy to overcome winter temperatures. In this work, we studied leaf senescence in yellow flag (Iris pseudacorus L.) individuals growing in a natural wetland, not only considering its relationship with external and internal cues, but also the plant developmental program, and the biological significance of rhizomes, storage organs that remain viable through winter. Total chlorophyll contents and the maximum efficiency of PSII (Fv /Fm ratio) decreased in senescing leaves, which was associated with a sharp increase in abscisic acid (ABA) contents. Furthermore, total cytokinin and 2-isopentenyladenine contents decreased in December compared to November, as plants became more stressed due to a decline in air temperatures. ABA increases in senescing leaves increased in parallel to reductions in violaxanthin. Rhizomes also accumulated large amounts of ABA during winter, while roots did not, and neither roots nor rhizomes accumulated 9-cis-epoxycarotenoids, thus suggesting ABA, which might play a role in conferring cold tolerance to this subterranean organ, may result from phloem transport from senescing leaves. It is concluded that (i) leaf senescence is a highly regulated physiological process in yellow flag playing a key role in the modulation of the entire plant developmental program, and (ii) ABA plays a major role not only in the regulation of leaf senescence but also in the establishment of cold tolerance in rhizomes, two processes that appear to be intimately interconnected.

The threshold between life and death in Cistus albidus L. seedlings: mechanisms underlying drought tolerance and resilience.

Drought can lead to important shifts in population dynamics if it occurs during seedling establishment. With the aim of elucidating the underlying mechanisms of drought tolerance and resilience, here we monitored the survival of seedlings of the Mediterranean shrub Cistus albidus L. throughout a year growing in the natural Park of the Montserrat Mountains (Spain) and, additionally, we studied the response to severe drought and subsequent recovery after rewatering of seedlings grown in growth chambers. To find possible mechanisms explaining how seedlings respond to drought, growth and survival together with physiological-related parameters such as chlorophyll contents, vitamin E and stress-related phytohormones were measured. We found that survival decreased by 30% at the end of summer and that the main proxy of seedling survival was total chlorophyll. This proxy was further confirmed in the growth chambers, where we found that seedlings that recovered from drought had higher levels of total chlorophyll compared with the seedlings that did not recover. Furthermore, modulation of vitamin E and jasmonates contents appeared to be crucial in the drought response of C. albidus seedlings. We propose a prediction model of survival that includes total chlorophyll height, leaf mass area and maximum photosystem II efficiency with chlorophyll contents being a good long-term predictor of C. albidus seedling survival under severe stress, which, in turn, could help to better foresee population fluctuations in the field.

Exemplar-based image inpainting using multiscale graph cuts.

We present a novel formulation of exemplar-based inpainting as a global energy optimization problem, written in terms of the offset map. The proposed energy function combines a data attachment term that ensures the continuity of reconstruction at the boundary of the inpainting domain with a smoothness term that ensures a visually coherent reconstruction inside the hole. This formulation is adapted to obtain a global minimum using the graph cuts algorithm. To reduce the computational complexity, we propose an efficient multiscale graph cuts algorithm. To compensate the loss of information at low resolution levels, we use a feature representation computed at the original image resolution. This permits alleviation of the ambiguity induced by comparing only color information when the image is represented at low resolution levels. Our experiments show how well the proposed algorithm performs compared with other recent algorithms.

Image editing with spatiograms transfer.

Histogram equalization is a well-known method for image contrast enhancement. Nevertheless, as histograms do not include any information on the spatial repartition of colors, their application to local image editing problems remains limited. To cope with this lack of spatial information, spatiograms have been recently proposed for tracking purposes. A spatiogram is an image descriptor that combines a histogram with the mean and the variance of the position of each color. In this paper, we address the problem of local retouching of images by proposing a variational method for spatiogram transfer. More precisely, a reference spatiogram is used to modify the color value of a given region of interest of the processed image. Experiments on shadow removal and inpainting demonstrate the strength of the proposed approach.

An Analysis of Visual Adaptation and Contrast Perception for Tone Mapping.

Tone Mapping is the problem of compressing the range of a High-Dynamic Range image so that it can be displayed in a Low-Dynamic Range screen, without losing or introducing novel details: The final image should produce in the observer a sensation as close as possible to the perception produced by the real-world scene. We propose a tone mapping operator with two stages. The first stage is a global method that implements visual adaptation, based on experiments on human perception, in particular we point out the importance of cone saturation. The second stage performs local contrast enhancement, based on a variational model inspired by color vision phenomenology. We evaluate this method with a metric validated by psychophysical experiments and, in terms of this metric, our method compares very well with the state of the art.

A comprehensive framework for image inpainting.

Inpainting is the art of modifying an image in a form that is not detectable by an ordinary observer. There are numerous and very different approaches to tackle the inpainting problem, though as explained in this paper, the most successful algorithms are based upon one or two of the following three basic techniques: copy-and-paste texture synthesis, geometric partial differential equations (PDEs), and coherence among neighboring pixels. We combine these three building blocks in a variational model, and provide a working algorithm for image inpainting trying to approximate the minimum of the proposed energy functional. Our experiments show that the combination of all three terms of the proposed energy works better than taking each term separately, and the results obtained are within the state-of-the-art.

Geometry-based demosaicking.

Demosaicking is a particular case of interpolation problems where, from a scalar image in which each pixel has either the red, the green or the blue component, we want to interpolate the full-color image. State-of-the-art demosaicking algorithms perform interpolation along edges, but these edges are estimated locally. We propose a level-set-based geometric method to estimate image edges, inspired by the image inpainting literature. This method has a time complexity of O(S) , where S is the number of pixels in the image, and compares favorably with the state-of-the-art algorithms both visually and in most relevant image quality measures.

An inpainting-based deinterlacing method.

Video is usually acquired in interlaced format, where each image frame is composed of two image fields, each field holding same parity lines. However, many display devices require progressive video as input; also, many video processing tasks perform better on progressive material than on interlaced video. In the literature, there exist a great number of algorithms for interlaced to progressive video conversion, with a great tradeoff between the speed and quality of the results. The best algorithms in terms of image quality require motion compensation; hence, they are computationally very intensive. In this paper, we propose a novel deinterlacing algorithm based on ideas from the image inpainting arena. We view the lines to interpolate as gaps that we need to inpaint. Numerically, this is implemented using a dynamic programming procedure, which ensures a complexity of O(S), where S is the number of pixels in the image. The results obtained with our algorithm compare favorably, in terms of image quality, with state-of-the-art methods, but at a lower computational cost, since we do not need to perform motion field estimation.

Movie denoising by average of warped lines.

Here, we present an efficient method for movie denoising that does not require any motion estimation. The method is based on the well-known fact that averaging several realizations of a random variable reduces the variance. For each pixel to be denoised, we look for close similar samples along the level surface passing through it. With these similar samples, we estimate the denoised pixel. The method to find close similar samples is done via warping lines in spatiotemporal neighborhoods. For that end, we present an algorithm based on a method for epipolar line matching in stereo pairs which has per-line complexity O (N), where N is the number of columns in the image. In this way, when applied to the image sequence, our algorithm is computationally efficient, having a complexity of the order of the total number of pixels. Furthermore, we show that the presented method is unsupervised and is adapted to denoise image sequences with an additive white noise while respecting the visual details on the movie frames. We have also experimented with other types of noise with satisfactory results.

Perceptual color correction through variational techniques.

In this paper, we present a discussion about perceptual-based color correction of digital images in the framework of variational techniques. We propose a novel image functional whose minimization produces a perceptually inspired color enhanced version of the original. The variational formulation permits a more flexible local control of contrast adjustment and attachment to data. We show that a numerical implementation of the gradient descent technique applied to this energy functional coincides with the equation of automatic color enhancement (ACE), a particular perceptual-based model of color enhancement. Moreover, we prove that a numerical approximation of the Euler-Lagrange equation reduces the computational complexity of ACE from theta(N2) to theta(N log N), where N is the total number of pixels in the image.

Morse description and geometric encoding of digital elevation maps.

Two complementary geometric structures for the topographic representation of an image are developed in this work. The first one computes a description of the Morse-topological structure of the image, while the second one computes a simplified version of its drainage structure. The topographic significance of the Morse and drainage structures of digital elevation maps (DEMs) suggests that they can been used as the basis of an efficient encoding scheme. As an application, we combine this geometric representation with an interpolation algorithm and lossless data compression schemes to develop a compression scheme for DEMs. This algorithm achieves high compression while controlling the maximum error in the decoded elevation map, a property that is necessary for the majority of applications dealing with DEMs. We present the underlying theory and compression results for standard DEM data.