40 research outputs found

    Subjective and objective evaluation of local dimming algorithms for HDR images

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    The preferred system gamma is primarily determined by the ratio of dynamic range of the original scene and the displayed image

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    The dynamic range of real world scenes may vary from around 102 to greater than 107 , whilst the dynamic range of monitors may vary from 102 to 105 . In this paper, we investigate the impact of the dynamic range ratio (DRratio) between the captured scene and the displayed image, upon the value of system gamma preferred by subjects (a simple global power law transformation applied to the image). To do so, we present an image dataset with a broad distribution of dynamic ranges upon various subranges of a SIM2 monitor. The full dynamic range of the monitor is 105 and we present images using either the full range, 75% or 50% of this, while maintaining a fixed mid-luminance level. We find that the preferred system gamma is inversely correlated with the DRratio and importantly, is one (linear) when the DRratio is one. This strongly suggests that the visual system is optimized for processing images only when the dynamic range is presented correctly. The DRratio is not the only factor. By using 50% of the monitor dynamic range and using either the lower, middle or upper portion of the monitor, we show that increasing the overall luminance level also increases the preferred system gamma, although to a lesser extent than the DR ratio

    Perceived dynamic range of HDR images

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    Although high dynamic range (HDR) imaging has gained great popularity and acceptance in both the scientific and commercial domains, the relationship between perceptually accurate, content-independent dynamic range and objective measures has not been fully explored. In this paper, a new methodology for perceived dynamic range evaluation of complex stimuli in HDR conditions is proposed. A subjective study with 20 participants was conducted and correlations between mean opinion scores (MOS) and three image features were analyzed. Strong Spearman correlations between MOS and objective DR measure and between MOS and image key were found. An exploratory analysis reveals that additional image characteristics should be considered when modeling perceptually-based dynamic range metrics. Finally, one of the outcomes of the study is the perceptually annotated HDR image dataset with MOS values, that can be used for HDR imaging algorithms and metric validation, content selection and analysis of aesthetic image attributes
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