An underwater image quality assessment metric

Various image enhancement algorithms are adopted to improve underwater images that often suffer from visual distortions. It is critical to assess the output quality of underwater images undergoing enhancement algorithms, and use the results to optimise underwater imaging systems. In our previous study, we created a benchmark for quality assessment of underwater image enhancement via subjective experiments. Building on the benchmark, this paper proposes a new objective metric that can automatically assess the output quality of image enhancement, namely UWEQM. By characterising specific underwater physics and relevant properties of the human visual system, image quality attributes are computed and combined to yield an overall metric. Experimental results show that the proposed UWEQM metric yields good performance in predicting image quality as perceived by human subjects

CUID: a new study of perceived image quality and its subjective assessment

Research on image quality assessment (IQA) remains limited mainly due to our incomplete knowledge about human visual perception. Existing IQA algorithms have been designed or trained with insufficient subjective data with a small degree of stimulus variability. This has led to challenges for those algorithms to handle complexity and diversity of real-world digital content. Perceptual evidence from human subjects serves as a grounding for the development of advanced IQA algorithms. It is thus critical to acquire reliable subjective data with controlled perception experiments that faithfully reflect human behavioural responses to distortions in visual signals. In this paper, we present a new study of image quality perception where subjective ratings were reliably collected in a controlled laboratory environment and for a large degree of stimulus content variability. We investigate how quality perception is affected by a combination of different categories of images and different types and levels of distortions. The database will be made publicly available to facilitate calibration and validation of IQA algorithms

Modulation of Dormancy and Growth Responses in Reproductive Buds of Temperate Trees

During autumn perennial trees cease growth and form structures called buds in order to protect meristems from the unfavorable environmental conditions, including low temperature and desiccation. In addition to increased tolerance to these abiotic stresses, reproductive buds modulate developmental programs leading to dormancy induction to avoid premature growth resumption, and flowering pathways. Stress tolerance, dormancy, and flowering processes are thus physically and temporarily restricted to a bud, and consequently forced to interact at the regulatory level. We review recent genomic, genetic, and molecular contributions to the knowledge of these three processes in trees, highlighting the role of epigenetic modifications, phytohormones, and common regulatory factors. Finally, we emphasize the utility of transcriptomic approaches for the identification of key structural and regulatory genes involved in bud processes, illustrated with our own experience using peach as a model

I Want to (Bud) Break Free: The Potential Role of DAM and SVP-Like Genes in Regulating Dormancy Cycle in Temperate Fruit Trees

Bud dormancy is an adaptive process that allows trees to survive the hard environmental conditions that they experience during the winter of temperate climates. Dormancy is characterized by the reduction in meristematic activity and the absence of visible growth. A prolonged exposure to cold temperatures is required to allow the bud resuming growth in response to warm temperatures. In fruit tree species, the dormancy cycle is believed to be regulated by a group of genes encoding MADS-box transcription factors. These genes are called DORMANCY-ASSOCIATED MADS-BOX (DAM) and are phylogenetically related to the Arabidopsis thaliana floral regulators SHORT VEGETATIVE PHASE (SVP) and AGAMOUS-LIKE 24. The interest in DAM and other orthologs of SVP (SVP-like) genes has notably increased due to the publication of several reports suggesting their role in the control of bud dormancy in numerous fruit species, including apple, pear, peach, Japanese apricot, and kiwifruit among others. In this review, we briefly describe the physiological bases of the dormancy cycle and how it is genetically regulated, with a particular emphasis on DAM and SVP-like genes. We also provide a detailed report of the most recent advances about the transcriptional regulation of these genes by seasonal cues, epigenetics and plant hormones. From this information, we propose a tentative classification of DAM and SVP-like genes based on their seasonal pattern of expression. Furthermore, we discuss the potential biological role of DAM and SVP-like genes in bud dormancy in antagonizing the function of FLOWERING LOCUS T-like genes. Finally, we draw a global picture of the possible role of DAM and SVP-like genes in the bud dormancy cycle and propose a model that integrates these genes in a molecular network of dormancy cycle regulation in temperate fruit trees

Naturalization of Screen Content Images for Enhanced Quality Evaluation

The quality assessment of screen content images (SCIs) has been attractive recently. Different from natural images, SCI is usually a mixture of picture and text. Traditional quality metrics are mainly designed for natural images, which do not fit well into the SCIs. Motivated by this, this letter presents a simple and effective method to naturalize SCIs, so that the traditional quality models can be applied for SCI quality prediction. Specifically, bicubic interpolation-based up-sampling is proposed to achieve this goal. Extensive experiments and comparisons demonstrate the effectiveness of the proposed method.Published versio