This paper presents an FPGA implementation of real-time high dynamic range (HDR) synthesis, which expresses a wide dynamic range by combining multiple images with different exposures using image pyramids. We have implemented a pipeline that performs streaming processing on images without using external memory. However, implementation for high-resolution images has been difficult due to large memory usage for line buffers. Therefore, we propose an image compression algorithm based on adaptive differential pulse code modulation (ADPCM). Compression modules based on the algorithm can be easily integrated into the pipeline. When the image resolution is 4K and the pyramid depth is 7, memory usage can be halved from 168.48% to 84.32% by introducing the compression modules, resulting in better quality.

A method for detecting the timing of photodiode (PD) saturation without using an in-pixel time-to-digital converter (TDC) is proposed. Detecting PD saturation time is an approach to extend the dynamic range of a CMOS image sensor (CIS) without multiple exposures. In addition to accumulated charges in a PD, PD saturation time can be used as a signal related to light intensity. However, in previously reported CISs with detecting PD saturation time, an in-pixel TDC is used to detect and store PD saturation time. That makes the resolution of a CIS lower because an in-pixel TDC requires a large area. As for the proposed pixel circuit, PD saturation time is detected and stored as a voltage in a capacitor. The voltage is read and converted to a digital code by a column ADC after an exposure. As a result, an in-pixel TDC is not required. A signal-processing and calibration method for combining two signals, which are saturation time and accumulated charges, linearly are also proposed. Circuit simulations confirmed that the proposed method extends the dynamic range by 36 dB and its total dynamic range to 95 dB. Effectiveness of the calibration was also confirmed through circuit simulations.

This paper proposes a lossless coding method for HDR color images stored in a floating point format called Radiance RGBE. In this method, three mantissa and a common exponent parts, each of which is represented in 8-bit depth, are encoded using the block-adaptive prediction technique with some modifications considering the data structure.

We propose a novel hue-correction scheme for multi-exposure image fusion (MEF). Various MEF methods have so far been studied to generate higher-quality images. However, there are few MEF methods considering hue distortion unlike other fields of image processing, due to a lack of a reference image that has correct hue. In the proposed scheme, we generate an HDR image as a reference for hue correction, from input multi-exposure images. After that, hue distortion in images fused by an MEF method is removed by using hue information of the HDR one, on the basis of the constant-hue plane in the RGB color space. In simulations, the proposed scheme is demonstrated to be effective to correct hue-distortion caused by conventional MEF methods. Experimental results also show that the proposed scheme can generate high-quality images, regardless of exposure conditions of input multi-exposure images.

High dynamic range (HDR) imaging refers to digital image processing that modifies the range of color and contrast to enhance image visibility. To create an HDR image, two or more images that include various information are needed. In order to convert low dynamic range (LDR) images to HDR images, we consider the possibility of using a generative adversarial network (GAN) as an appropriate deep neural network. Deep learning requires a great deal of data in order to build a module, but once the module is created, it is convenient to use. In this paper, we propose a weight map for local luminance based on learning to reconstruct locally tone-mapped images.

We aim at HDR imaging with simple processing while preventing spatial resolution degradation in multiple-exposure-time image sensor where the exposure time is controlled for each pixel. The contributions are the proposal of image interpolation by motion area detection and pixel adaptive weighting method by overexposure and motion blur detection.

We propose an efficient two-layer near-lossless coding method using an extended histogram packing technique with backward compatibility to the legacy JPEG standard. The JPEG XT, which is the international standard to compress HDR images, adopts a two-layer coding method for backward compatibility to the legacy JPEG standard. However, there are two problems with this two-layer coding method. One is that it does not exhibit better near-lossless performance than other methods for HDR image compression with single-layer structure. The other problem is that the determining the appropriate values of the coding parameters may be required for each input image to achieve good compression performance of near-lossless compression with the two-layer coding method of the JPEG XT. To solve these problems, we focus on a histogram-packing technique that takes into account the histogram sparseness of HDR images. We used zero-skip quantization, which is an extension of the histogram-packing technique proposed for lossless coding, for implementing the proposed near-lossless coding method. The experimental results indicate that the proposed method exhibits not only a better near-lossless compression performance than that of the two-layer coding method of the JPEG XT, but also there are no issue regarding the combination of parameter values without losing backward compatibility to the JPEG standard.

An efficient two-layer coding method using the histogram packing technique with the backward compatibility to the legacy JPEG is proposed in this paper. The JPEG XT, which is the international standard to compress HDR images, adopts two-layer coding scheme for backward compatibility to the legacy JPEG. However, this two-layer coding structure does not give better lossless performance than the other existing methods for HDR image compression with single-layer structure. Moreover, the lossless compression of the JPEG XT has a problem on determination of the coding parameters; The lossless performance is affected by the input images and/or the parameter values. That is, finding appropriate combination of the values is necessary to achieve good lossless performance. It is firstly pointed out that the histogram packing technique considering the histogram sparseness of HDR images is able to improve the performance of lossless compression. Then, a novel two-layer coding with the histogram packing technique and an additional lossless encoder is proposed. The experimental results demonstrate that not only the proposed method has a better lossless compression performance than that of the JPEG XT, but also there is no need to determine image-dependent parameter values for good compression performance without losing the backward compatibility to the well known legacy JPEG standard.

High dynamic range (HDR) images contain more details of the scene as compared to commonly used low dynamic range (LDR) images. The additional information in the HDR images is important for applications such as high-quality graphics rendering, sensing, scene analysis, and surveillance etc. Moreover, HDR images would provide better visualization experience on HDR displays, which might become more common in near future. Therefore, it is important to encode the entire dynamic range of the HDR images. In this paper, a new lossless, four-channel, eight bits per channel, format for encoding floating-point HDR images is proposed. The format is similar to the well-known RGBE format but constructs the E channel differently for better accuracy. Experimental results show that our technique could reduce the rounding error of the RGBE by more than 88%. In addition, there was a reduction of 44.3% in average error for all 33 images in the database used for this study.

In this paper, we propose a 2-layer lossless coding method for high dynamic range (HDR) images based on range compression and adaptive inverse tone-mapping. Recently, HDR images, which have a wider range of luminance than conventional low dynamic range (LDR) ones, have been frequently used in various fields. Since commonly used devices cannot yet display HDR images, 2-layer coding methods that decode not only HDR images but also their LDR versions have been proposed. We have previously proposed a state-of-the-art 2-layer lossless coding method for HDR images that unfortunately has huge HDR file size. Hence, we introduce two ideas to reduce the HDR file size to less than that of the previous method. The proposed method achieves high compression ratio and experiments show that it outperforms the previous method and other conventional methods.

This paper proposes a new inverse tone mapping operator (TMO) with estimated parameters. The proposed inverse TMO is based on Reinhard's global operator which is a well-known TMO. Inverse TM operations have two applications: generating an HDR image from an existing LDR one, and reconstructing an original HDR image from the mapped LDR image. The proposed one can be applied to both applications. In the latter application, two parameters used in Reinhard's TMO, i.e. the key value α regarding brightness of a mapped LDR one and the geometric mean $overline{L}_w$ of an original HDR one, are generally required for carrying out the Reinhard based inverse TMO. In this paper, we show that it is possible to estimate $overline{L}_w$ from α under some conditions, while α can be also estimated from $overline{L}_w$, so that a new inverse TMO with estimated parameter is proposed. Experimental results show that the proposed method outperforms conventional ones for both applications, in terms of high structural similarities and low computational costs.

High-dynamic-range imaging (HDRI) technologies aim to extend the dynamic range of luminance against the limitation of camera sensors. Irradiance information of a scene can be reconstructed by fusing multiple low-dynamic-range (LDR) images with different exposures. The key issue is removing ghost artifacts caused by motion of moving objects and handheld cameras. This paper proposes a robust ghost-free HDRI algorithm by visual salience based bilateral motion detection and stack extension based exposure fusion. For ghost areas detection, visual salience is introduced to measure the differences between multiple images; bilateral motion detection is employed to improve the accuracy of labeling motion areas. For exposure fusion, the proposed algorithm reduces the discontinuity of brightness by stack extension and rejects the information of ghost areas to avoid artifacts via fusion masks. Experiment results show that the proposed algorithm can remove ghost artifacts accurately for both static and handheld cameras, remain robust to scenes with complex motion and keep low complexity over recent advances including rank minimization based method and patch based method by 63.6% and 20.4% time savings averagely.

The problem of reproducing high dynamic range (HDR) images on devices with a restricted dynamic range has gained a lot of interest in the computer graphics community. Various approaches to this issue exist, spanning several research areas, including computer graphics, image processing, color vision, and physiology. However, most of the approaches to the issue have several serious well-known color distortion problems. Accordingly, this article presents a tone-mapping method. The proposed method comprises the tone-mapping operator and the chromatic adaptation transform. The tone-mapping method is combined with linear and non-linear mapping using visual gamma based on contrast sensitive function (CSF) and using key of scene value, where the visual gamma is adopted to automatically control the dynamic range, parameter free, as well as to avoid both the luminance shift and the hue shift in the displayed images. Furthermore, the key of scene value is used to represent whether the scene was subjectively light, norm, dark. The resulting image is then processed through a chromatic adaptation transform and emphasis lies in human visual perception (HVP). The experiment results show that the proposed method yields better performance of the color rendering over the conventional method in subjective and quantitative quality and color reproduction.

A number of successful tone mapping operators (TMOs) for contrast compression have been proposed due to the need to visualize high dynamic range (HDR) images on low dynamic range devices. This paper proposes a novel inverse tone mapping (TM) operation and a new remapping framework with the operation. Existing inverse TM operations require either the store of some parameters calculated in forward TM, or data-depended operations. The proposed inverse TM operation enables to estimate HDR images from LDR ones mapped by the Reinhard's global operator, not only without keeping any parameters but also without any data-depended calculation. The proposed remapping framework with the inverse operation consists of two TM operations. The first TM operation is carried out by the Reinhard's global operator, and then the generated LDR one is stored. When we want different quality LDR ones, the proposed inverse TM operation is applied to the stored LDR one to generate an HDR one, and the second TM operation is applied to the HDR one to generate an LDR one with desirable quality, by using an arbitrary TMO. This framework allows not only to visualize an HDR image on low dynamic range devices at low computing cost, but also to efficiently store an HDR one as an LDR one. In simulations, it is shown that the proposed inverse TM operation has low computational cost, compared to the conventional ones. Furthermore, it is confirmed that the proposed framework allows to remap the stored LDR one to another LDR one whose quality is the same as that of the LDR one remapped by the conventional inverse TMO with parameters.

The iCAM06 has been used as an image appearance model for HDR image rendering. iCAM06 goes through the color space conversions of the several steps to present HDR images. The dynamic range of a HDR image needs to be mapped onto the range of output devices, which is called the tone mapping. However, tone compression process of iCAM06 causes white point shift and color distortion because of color-clipping and cross-stimulus. Therefore, we proposed a modified white-balanced method in low-chromatic region and a color adjustment method in IPT space to compensate the color distortion during in tone compression process. Through the experimental results, we confirmed the proposed compatible color adjustment method had better performance than iCAM06 and enhanced models.

Many High-Dynamic-Range (HDR) rendering techniques have been developed. Of these, the image color appearance model, iCAM, is a typical HDR image rendering algorithm. HDR rendering methods normally require a tone compression process and include many color space transformations from the RGB signal of an input image to the RGB signal of output devices for the realistic depiction of a captured image. The iCAM06, which is a refined iCAM, also contains a tone compression step and several color space conversions for HDR image reproduction. On the other hand, the tone compression and frequent color space changes in the iCAM06 cause color distortion, such as a hue shift and saturation reduction of the output image. To solve these problems, this paper proposes a separate color correction method that has no effect on the output luminance values by controlling only the saturation and hue of the color attributes. The color saturation of the output image was compensated for using the compensation gain and the hue shift was corrected using the rotation matrix. The separate color correction method reduces the existing color changes in iCAM06. The compensation gain and rotation matrix for the color correction were formulated based on the relationship between the input and output tristimulus values through the tone compression. The experimental results show that the revised iCAM06 with the proposed method has better performance than the default iCAM06.

Due to the growing popularity of High Dynamic Range (HDR) images and HDR displays, a large amount of existing Low Dynamic Range (LDR) images are required to be converted to HDR format to benefit HDR advantages, which give rise to some LDR to HDR algorithms. Most of these algorithms especially tackle overexposed areas during expanding, which is the potential to make the image quality worse than that before processing and introduces artifacts. To dispel these problems, we present a new LDR to HDR approach, unlike the existing techniques, it focuses on avoiding sophisticated treatment to overexposed areas in dynamic range expansion step. Based on a separating principle, firstly, according to the familiar types of overexposure, the overexposed areas are classified into two categories which are removed and corrected respectively by two kinds of techniques. Secondly, for maintaining color consistency, color recovery is carried out to the preprocessed images. Finally, the LDR image is expanded to HDR. Experiments show that the proposed approach performs well and produced images become more favorable and suitable for applications. The image quality metric also illustrates that we can reveal more details without causing artifacts introduced by other algorithms.

In this letter, a precoding design for a multiple-input multiple-output (MIMO) full-duplex relay (FDR) system is proposed. For this system, mitigating the self-interference imposed by the transmit antennas on the receive antennas in the same relay station is crucial for improving the performance of the FDR system. The precoding scheme designed in this study uses block-diagonalization (BD). Using this precoding scheme, FDR capacity analysis is performed in the MIMO downlink relay system. Numerical results on system performance in terms of capacity are shown and discussed.

High Dynamic Range (HDR) images have been widely applied in daily applications. However, HDR image is a special format, which needs to be pre-processed known as tone mapping operators for display. Since the visual quality of HDR images is very sensitive to luminance value variations, conventional watermarking methods for low dynamic range (LDR) images are not suitable and may even cause catastrophic visible distortion. Currently, few methods for HDR image watermarking are proposed. In this paper, two watermarking schemes targeting HDR images are proposed, which are based on µ-Law and bilateral filtering, respectively. Both of the subjective and objective qualities of watermarked images are greatly improved by the two methods. What's more, these proposed methods also show higher robustness against tone mapping operations.

In this paper, we propose a coding algorithm for High Dynamic Range Images (HDRI). Our encoder applies a tone mapping model based on scaled µ-Law encoding, followed by a conventional Low Dynamic Range Image (LDRI) encoder. The tone mapping model is designed to minimize the difference between the tone-mapped HDRI and its LDR version. By virtue of the nature of the µ-Law model, not only the quality of the HDRI but also the one of the LDRI is improved, compared with a state of the art in conventional HDRI coding methods. Furthermore the error limit caused by our encoding is theoretically analyzed.