DSLR-Quality Photos on Mobile Devices with Deep Convolutional Networks

Despite a rapid rise in the quality of built-in smartphone cameras, their physical limitations - small sensor size, compact lenses and the lack of specific hardware, - impede them to achieve the quality results of DSLR cameras. In this work we present an end-to-end deep learning approach that bridges this gap by translating ordinary photos into DSLR-quality images. We propose learning the translation function using a residual convolutional neural network that improves both color rendition and image sharpness. Since the standard mean squared loss is not well suited for measuring perceptual image quality, we introduce a composite perceptual error function that combines content, color and texture losses. The first two losses are defined analytically, while the texture loss is learned in an adversarial fashion. We also present DPED, a large-scale dataset that consists of real photos captured from three different phones and one high-end reflex camera. Our quantitative and qualitative assessments reveal that the enhanced image quality is comparable to that of DSLR-taken photos, while the methodology is generalized to any type of digital camera

A Study of the color management implementation on the RGB-based digital imaging workflow: digital camera to RGB printers

An RGB (red, green, and blue color information) workflow is used in digital photography today because a lot of the devices digital cameras, scanners, monitors, image recorders (LVT or Light Value Technology), and some types of printers are based on RGB color information. In addition, rapidly growing new media such as the Internet and CD-ROM (Compact Disc-Read-Only Memory) publishing use an RGB -based monitor as the output device. Because color is device-dependent, each device has a different method of representing color information. Each has a different range of color they can reproduce. Most of the time, the range of color, color gamut, that devices can produce is smaller than that of the original capturing device. As a result, a color image reproduction does not match accurately with its original. Therefore, in typical color image reproduction, the task of matching a color image reproduction with its original is a significant problem that operators must overcome to achieve good quality color image reproduction. Generally, there are two approaches to conquer these problems. The first method is trial-and-error in the legacy-based system. This method is effective in a pair-wise working environment and highly depended on a skill operator. The second method is the ICC-based (ICC or International Color Consortium) color management system (CMS) which is more practical in the multiple devices working environment. Using the right method leads to the higher efficiency of a digital photography produc tion. Therefore, the purpose of this thesis project is to verify that ICC-based CMS with an RGB workflow has higher efficiency (better utilized of resource and capacity) than a legacy-based traditional color reproduction workflow. In this study, the RGB workflows from digital cameras to RGB digital printers were used because of the increasing num ber of digital camera users and the advantages of using an RGB workflow in digital pho tography. There were two experimental image reproduction workflows the legacy-based system and the ICC-based color management system. Both of them used the same raw RGB images that were captured from digital cameras as their input files. The color images were modified with two different color matching methods according to each workflow. Then, they were printed out to two RGB digital printers. Twenty observers were asked to evaluate the picture quality as well as the reproduction quality. The results demonstrated that the two workflows had the ability to produce an accept able picture quality reproduction. For reproduction quality aspect, the reproductions of the ICC-based CMS workflow had higher reproduction quality than the legacy-based workflow. In addition, when the time usage of the workflow was taken into account, it showed that the ICC-based CMS had higher efficiency than the legacy-based system. However, many times, image production jobs do not start with optimum quality raw images as in this study; for example, they are under/over exposure or have some defects. These images need some retouching work or fine adjustment to improve their quality. In these cases, the ICC-based CMS with skilled operators can be implemented to these types of production in order to achieve the high efficiency workflow

An Investigation into the application of digital camera created images and their preparation for newspaper lithographic reproduction without a reference analog reflection or transmission original

Looking at the shoes that digital photography has a role in filling we can quickly see performance issues that will undoubtedly affect our final printed reproduction. The resolution provided by a digital image is directly correlated to the CCD size, quality and any associated post-imaging processes provided by cam era manufacturers but is only one of quality-limiting factors involved in digital photography. Silicon-based CCD\u27s are monochrome in nature. \u27 Having the inability to decipher the varying degrees of red, green and blue light presented to the pixels it is necessary to account for RGB light by introducing a color-filtering method. The color-filtering method prevalent in the cameras to be tested are referred to as integral color filter arrays (CFA). 2 Integral color filter arrays performs color filtering on the chip with each individual pixel hosting a specific filter color (red, green or blue). This allows for the deciphering of the various light wavelengths presented in a scene to be translated by the CCD into digitized values of color, but because each pixel can only represent one filter color this results in problems including; the loss of information leading to reduced effective resolution and increased sampling (quantizing) artifacts. 3 Such color-gathering techniques and various inherent CCD issues account for problems that must be addressed and minimized during post-image processing prepress steps. The following endeavor is to evaluate three types of digital cameras (Minolta RD-175, Fuji 505a, AP NC2000e/Canon DCS EOS3) which can meet the requirements of a photojournalist then identifying the various issues that are inherent to each camera, post processing prepress solutions will be sought through the use of Adobe Photoshop. By evaluating the cameras via tests that provide information about resolution, dynamic range, color gamut reproduction abilities and image-to-noise relationships it was possible to assess what cam era shortcomings must be addressed during post-image processing. The shortcomings were then individually assessed and, utilizing prepress skills post-processing procedures, were identified to address the specific inherent shortcomings. Using SNAP (specifications for non-heat advertising printing) specifications, a representative set of images were printed and analyzed. The results from this analysis presents camera performance issues prior to post-image processing optimization and after post-image processing optimization. It will illustrate the initial shortcomings and how well these shortcomings can be de-emphasized in Adobe Photoshop. The printing of test images to SNAP specifications also illustrates if there is any loss of quali ty due to the reproduction on newsprint. Based on the test performed it was established that each usable camera ISO has its own specific set of characteristics that effect visual resolution, color gamut, usable range and noise. The method the man ufacturer uses to acquire its images, including CCD hardware, camera firmware and pre-acquire pro cessing, also affect visual resolution, color gamut, usable range, noise and aliasing. Photographic metering techniques and photographer criteria for ISO selection can assist in main taining the highest level of exposure quality capable for each camera. When the highest level of image quality is achieved with the use of photographic techniques, the highest level of visual resolution, color gamut, usable range and the least noise can be rendered for each camera image. Knowledge of Adobe Photoshop and offset printing principles, such as memory colors, wanted and unwanted colors, are valuable in enhancing the digital camera\u27s limited color gamut. The nature of the newspaper printing process produces a small color gamut, therefore, the limited gamut inherent in the digital cameras is of less concern than if the digital images were printed using a larger color gamut capa ble four-color process. The identification of each camera\u27s tendencies does allow for a greater understanding of applic able procedures within Adobe Photoshop which can reduce and or alleviate the tendencies

High performance image demosaicing hardware designs

Most digital cameras capture only one color channel (red, green, or blue) per pixel, because capturing three color channels per pixel would require three image sensors which increases the cost of digital cameras. Therefore, only one image sensor is used, and images pass through a color filter array (CFA) before being captured by the image sensor. Bayer pattern is the most commonly used CFA pattern in digital cameras. Demosaicing is the process of reconstructing the missing color channels of the pixels in the color filtered image using their available neighboring pixels. There are many image demosaicing algorithms with varying reconstructed image quality and computational complexity. In this thesis, high performance hardware architectures are designed for three high quality image demosaicing algorithms, and the proposed hardware architectures are implemented on FPGA. A high performance hardware architecture for Effective Color Interpolation (ECI) demosaicing algorithm is proposed. A modified version of Enhanced ECI demosaicing algorithm and a high performance hardware architecture for this image demosaicing algorithm are proposed. A hybrid ECI and Alternating Projections demosaicing algorithm and a high performance hardware architecture for this image demosaicing algorithm are proposed. The proposed hardware architectures are implemented using Verilog HDL. The Verilog RTL codes are mapped to Xilinx Virtex 6 FPGA. The proposed FPGA implementations are verified with post place & route simulations. They are capable of processing 160, 118, and 119 full HD images per second

IMAGE QUALITY IMPROVEMENT BY ADAPTIVE EXPOSURE CORRECTION TECHNIQUES

The proposed paper concerns the processing of images in digital format and, more specifically, particular techniques that can be advantageously used in digital still cameras for improving the quality of images acquired with a non-optimal exposure. The proposed approach analyses the CCD/CMOS sensor Bayer data or the corresponding color generated image and, after identifying specific features, it adjusts the exposure level according to a ‘camera response ’ like function. 1

A testing procedure to characterize color and spatial quality of digital cameras used to image cultural heritage

A testing procedure for characterizing both the color and spatial image quality of trichromatic digital cameras, which are used to photograph paintings in cultural heritage institutions, is described. This testing procedure is target-based, thus providing objective measures of quality. The majority of the testing procedure followed current standards from national and international organizations such as ANSI, ISO, and IEC. The procedure was developed in an academic research laboratory and used to benchmark four representative American museum’s digital-camera systems and workflows. The quality parameters tested included system spatial uniformity, tone reproduction, color reproduction accuracy, noise, dynamic range, spatial cross-talk, spatial frequency response, color-channel registration, and depth of field. In addition, two paintings were imaged and processed through each museum’s normal digital workflow. The results of the four case studies showed many dissimilarities among the digital-camera systems and workflows of American museums, which causes a significant range in the archival quality of their digital masters

Demosaicing of Color Images by Accurate Estimation of Luminance

Digital cameras acquire color images using a single sensor with Color filter Arrays. A single color component per pixel is acquired using color filter arrays and the remaining two components are obtained using demosaicing techniques. The conventional demosaicing techniques existent induce artifacts in resultant images effecting reconstruction quality. To overcome this drawback a frequency based demosaicing technique is proposed. The luminance and chrominance components extracted from the frequency domain of the image are interpolated to produce intermediate demosaiced images. A novel Neural Network Based Image Reconstruction Algorithm is applied to the intermediate demosaiced image to obtain resultant demosaiced images. The results presented in the paper prove the proposed demosaicing technique exhibits the best performance and is applicable to a wide variety of images

High performance high quality image demosaicing hardware designs

Since capturing three color channels (red, green, and blue) per pixel increases the cost of digital cameras, most digital cameras capture only one color channel per pixel using a single image sensor. The images pass through a color filter array before being captured by the image sensor. Demosaicing is the process of reconstructing the missing color channels of the pixels in the color filtered image using their available neighboring pixels. There are many image demosaicing algorithms with varying reconstructed image quality and computational complexity. In this thesis, high performance hardware architectures are designed for two high quality image demosaicing algorithms with high computational complexity. The proposed hardware architectures are implemented on an FPGA. A high performance Alternating Projections (AP) image demosaicing hardware is proposed. This is the first AP image demosaicing hardware in the literature. A high performance Enhanced Effective Color Interpolation (EECI) image demosaicing hardware is proposed. This is the first EECI image demosaicing hardware in the literature. The proposed hardware architectures are implemented using Verilog HDL. The Verilog RTL codes are mapped to a Xilinx Virtex 6 FPGA. The proposed FPGA implementations are verified with post place & route simulations. They can process 31 and 94 full HD (1920x1080) images per second, respectively