Gradient-Based Synthesized Multiple Exposure Time Color HDR Image

Várkonyi-Kóczy, Annamária R.; Rövid, András; Hashimoto, Takeshi

doi:10.1109/tim.2008.925715

Cited by 55 publications

(19 citation statements)

References 8 publications

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“…5 decades or more, which greatly exceeds the range of linear operation of most of the image sensors. Instead of using multiple exposures to acquiring all the detail information in different ranges [5], the proposed procedure is designed to extract the information from an image acquired or transferred by range-limited devices. To enhance or restore the edge gradients, different degrees of signal attenuation in the regions under different intensity conditions need to be investigated.…”

Section: Design Of Filtering Processesmentioning

confidence: 99%

“…The outputs of this stage are the images SI D , SI M and SI B , with SIs standing for the selected images. (5) In each of the SIs, the threshold value is determined by the average value of all the non-zero pixels and applied to this SI to perform binarization. After a thinning process, three edge maps EM D , EM M and EM B are then generated and merged.…”

Section: Figmentioning

confidence: 99%

“…In case of processing HDR images, multiple exposures can be used to generate several images. Detailed information is captured in a series of images, and a fusion algorithm is developed to merge them [4] [5].…”

Section: Introductionmentioning

confidence: 99%

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Multiple-filtering process and its application in edge detection

Wang

2009

2009 52nd IEEE International Midwest Symposium on Circuits and Systems

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In this paper, a procedure of edge detection for a high dynamic range image with damaged edge information is proposed. This procedure is based on a scheme of multiple filtering processes which does not include any segmentation of the image. Three different filtering processes are designed to generate three gradient maps, in each of which gradients are calculated and modulated by using a specific filter. The enhanced gradients, i.e. those modulated correctly, are identified in each of the three gradient maps by using a selection algorithm. They are taken to generate a complete edge map. This procedure allows varieties of edge gradient enhancements applied in the same image by employing a set of simple filters without segmentation. The effectiveness of the detection process has been confirmed by simulations.Index Terms-multiple-filtering, edge detection, high dynamic range image, gradient magnitude based detection

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Section: Design Of Filtering Processesmentioning

confidence: 99%

Section: Figmentioning

confidence: 99%

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Multiple-filtering process and its application in edge detection

Wang

2009

2009 52nd IEEE International Midwest Symposium on Circuits and Systems

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“…First, we measure the sum of the gradients of the luminance component as a spatial complexity metric. 4 Let ⌬Y h and ⌬Y v denote the horizontal and vertical gradient defined as…”

Section: Proposed Algorithmmentioning

confidence: 99%

Adaptive quarter-pel motion estimation and motion vector coding algorithm for the H.264/AVC standard

Jung

Park

et al. 2009

Opt. Eng

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Abstract. We present an adaptive quarter-pel ͑Qpel͒ motion estimation ͑ME͒ method for H.264/AVC. Instead of applying Qpel ME to all macroblocks ͑MBs͒, the proposed method selectively performs Qpel ME in an MB level. In order to reduce the bit rate, we also propose a motion vector ͑MV͒ encoding technique that adaptively selects a different variable length coding ͑VLC͒ table according to the accuracy of the MV. Experimental results show that the proposed method can achieve about 3% average bit rate reduction.

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“…HDR digital photography was first developed nearly two decades ago, a variation first developed by Mann [1]. Multiple exposure methods [2][3][4][5] are commonly used to expand the dynamic range. Three images obtained using three different exposures can be merged using gradient-based synthesis [4].…”

Section: Introductionmentioning

confidence: 99%

High‐performance high dynamic range image generation by inverted local patterns

Hsia¹,

Kuo²

2015

IET Image Processing

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This study presents an image processing algorithm capable of generating high dynamic range (HDR) images from a single frame. On the basis of liquid crystal display (LCD) backlight theory, the proposed algorithm uses an inverted local pattern approach to adjust the histogram of lighting distribution. To improve processing efficiency, sampled images are classified into three types according to exposure characteristics, which are used to obtain suitable processing factor. The inverting factor is mixed with the original sample to darken the bright areas and brighten the dark areas in the images. Brightness enhancement and auto-gain control are then added to expand the range of the grey levels. Authors' results demonstrate the efficacy of the proposed HDR algorithm in improving shadow details. In addition, single-pass processing is used to reduce computational complexity, making the algorithm applicable for lowpower portable cameras and video recorders.

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Gradient-Based Synthesized Multiple Exposure Time Color HDR Image

Cited by 55 publications

References 8 publications

Multiple-filtering process and its application in edge detection

Multiple-filtering process and its application in edge detection

Adaptive quarter-pel motion estimation and motion vector coding algorithm for the H.264/AVC standard

High‐performance high dynamic range image generation by inverted local patterns

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