技巧SHORTCUTS：PHOTOSHOP

在这里．我们将探讨色阶(Level)的一种替代方法。这是一个非常简单的技巧．可以对图像进行类似色阶的调节。而且只用到图层。同时．使用这种方法生成的效果在Photoshop的色阶对话框中是无法达到的。     

在Photoshop中使用吸管法进行图像颜色校正

结合实例从颜色工作机制、灰度修正与专业颜色校正等方面，介绍使用Photoshop“曲线”或“色阶”对话框中的黑场、灰场和白场吸管进行图像颜色校正的过程与方法．指出用吸管法进行校色的优势所在。     

基于暗通道先验和优化自动色阶的图像去雾算法

针对暗通道先验产生的图像深度边缘上的白色晕圈、天空区域失真等问题,提出基于暗通道先验和优化自动色阶的单图像去雾算法.引入改进暗通道先验对透射率进行导向滤波,精细化透射率传播图,利用加权最小二乘法保留图像边缘信息,以优化自动色阶增强图像.采用定性与定量分析相结合的方法对该算法和几种经典去雾算法进行评价,结果表明该算法能够在保持图像颜色质量的同时保留细节清晰,具有更好的视觉感知.     

基于局部线性变换的色阶映射算法

为了提高高动态图像显示的视觉效果,提出了一种基于局部线性变换的色阶映射算法;针对图像直接线性压缩能力较差的缺点,本文提出一种局部的线性变换模型;由于局部窗的结构,是利用局部窗的中心像素点与窗内的其他像素点的均值,方差的关系构造而成,因此基于局部线性变换的色阶映射算法能够抑制由具有高对比度的图像边缘所引起的鬼影和光晕现象;首先,根据线性变换将图像的色阶映射转换为求解泛函的最优解;其次,通过推导求解出线性变换的参数并将泛函最优化问题转换为求解一个线性方程组问题;最后求解线性方程组,得出视觉效果较好的低动态范围图像;有效避免传统色阶映射出现的光晕和亮度不连续的现象,能够更多的保留高动态图像的细节;最后通过实验结果对比分析,通过信息熵和对比度两个参数可以体现文中算法较好。     

使用Photoshop CS4快速调出照片柔和暗黄色效果

本文主要讲解在Photoshop中使用“色阶”命令来对照片进行调色，从而改变照片的效果。主要用到了Photoshop的选区羽化和色阶命令。     

基于色阶重建的彩色图像增强算法

色阶重建技术已应用于高动态范围图像的处理中.应用色调映射技术和局部亮度适应性原理,提出了彩色图像增强的算法来改善彩色图像的可视性.使用一个参数自适应的可变基的对数函数对亮度图像进行变换,采用双边滤波技术来计算每一像素的局部适应亮度,再对彩色图像的对比度进行调整.实验结果显示,图像的暗区部分获得了较好的可视性和细节,同时对比度获得改善.     

色外观匹配的高动态范围图像再现

针对高动态范围(high dynamic range,HDR)图像再现因观察条件变化引起的再现图像与源图像色外观不一致问题,提出一种色外观匹配的HDR图像再现算法.首先将HDR图像的色度和亮度信息分离,通过估计源场景观察条件,利用色外观模型(color appearance model,CAM)将HDR图像再现至显示环境,保持源场景的色度外观;然后针对亮度图像,根据直方图特征进行自适应分区,构造分段线性色阶调整函数,将显示亮度范围动态分配给不同的亮度分区,以增强图像感知对比度,并利用双边滤波技术提取图像细节信息进行细节补偿;最后,将处理后的彩色和非彩色信息合成,并对亮度压缩带来的色外观变化进行色度校正,得到与源HDR图像色外观一致的低动态范围(low dynamic range,LDR)再现图像.实验表明,新算法在色外观保持、动态范围压缩和细节表现上均优于传统算法.     

基于颜色与结构失真的色域映射图像无参考质量评价算法

为了预测色域映射图像客观质量,通过分析不同色域映射算法的映射原理发现色域映射图像中主要存在颜色失真与结构失真的情况.基于此,提出了一种基于颜色与结构失真的色域映射图像无参考质量评价算法.在颜色失真方面,计算色调异常率和图像R、G、B三个分量的统计分布与理想均匀分布之间的相对熵;在结构退化方面,提取图像的信息熵与四阶矩,并对图像亮度与饱和度进行统计建模,提取参数特征.随后,将以上提取的数据作为质量感知特征与图像的主观分数值输入后向传播神经网络进行回归训练得到针对色域映射图像的质量评价模型.最后,在三个公开的色域映射图像数据库上进行性能验证.实验结果表明,该算法在预测色域映射图像质量方面优于现有的无参考算法.     

Photoshop色阶与曲线工具功能异同及其优选研究

Photoshop是众多的图像处理软件中功能比较强大应用比较广泛的一款软件,其中,色阶和曲线是最基本、最惯用的Photoshop用具。本文亦是以介绍色阶和曲线用具的相关信息为主,谈到了色阶和曲线的基本概念、必要认识、它们各自功能的介绍、分析其功能的异同以及其优先选用原则等。以便在今后的应用中针对不同的调整效果选择不同的用具。     

基于改进暗通道先验的交通图像去雾新方法

针对交通场景图像中由于雾霾导致的图像目标主体不清晰,影响监控效果的问题,提出一种基于导向滤波与自适应色阶调整的改进暗通道图像去雾新方法.首先,基于暗通道原理对原始图像进行映射处理,从而得到大气光成分与透射率的估计值,并利用多维导向滤波方法对大气透射率估计值进行优化处理;然后,根据图像降质过程的逆过程,求解雾霾图像清晰化处理初始结果;最后,利用多通道自适应色阶调整方法进一步优化初始结果,解决初始结果整体亮度较暗、不利于监控系统后期处理的问题.实验结果表明,清晰化处理后的图像具有较高的亮度和对比度值,较好地保留并增强了图像的边缘和细节信息,算法去雾霾效果显著,针对交通场景图像处理的自适应性较高.     

基于 TD_SCDMA 电子相框的照片分享方案

随着数码相机的普及,拍摄的数码照片呈几何级数增加,除了少部分会被冲洗成纸质照片以外,大部分数码照片都会被保存在电子存储设备中。电子相框是非常适合的存储设备,兼具展示数码照片的功能,近年来正在蓬勃发展。本文分析了电子相框发展的现状和业务需求,针对传统电子相框面临照片更新与共享的问题,提出了一种基于TD_SCDMA（Time Division-Synchronous Code Division Multiple Access）的照片分享方案,将电子相框接入UMTS（Universal Mobile Telecommunications System,通用移动通信系统）,采用电子相框统一服务平台实现了照片在手机、电脑和电子相框之间的无缝分享。     

Multi-modal and multi-scale photo collection summarization

With the proliferation of digital cameras and mobile devices, people are taking much more photos than ever before. However, these photos can be redundant in content and varied in quality. Therefore there is a growing need for tools to manage the photo collections. One efficient photo management way is photo collection summarization which segments the photo collection into different events and then selects a set of representative and high quality photos (key photos) from those events. However, existing photo collection summarization methods mainly consider the low-level features for photo representation only, such as color, texture, etc, while ignore many other useful features, for example high-level semantic feature and location. Moreover, they often return fixed summarization results which provide little flexibility. In this paper, we propose a multi-modal and multi-scale photo collection summarization method by leveraging multi-modal features, including time, location and high-level semantic features. We first use Gaussian mixture model to segment photo collection into events. With images represented by those multi-modal features, our event segmentation algorithm can generate better performance since the multi-modal features can better capture the inhomogeneous structure of events. Next we propose a novel key photo ranking and selection algorithm to select representative and high quality photos from the events for summarization. Our key photo ranking algorithm takes the importance of both events and photos into consideration. Furthermore, our photo summarization method allows users to control the scale of event segmentation and number of key photos selected. We evaluate our method by extensive experiments on four photo collections. Experimental results demonstrate that our method achieves better performance than previous photo collection summarization methods.     

Photoshop图层混合模式详解及应用

图层混合模式是Photoshop的精华,有着非常强大的功能,是当前图层与下方图层图像进行混合的模式,利用图层的混合模式可以轻松地制作出独特的图像效果。详细介绍了Photoshop图层混合模式及其作用,如正常模式和溶解模式、变暗模式组、变亮模式组、对比模式组、对照模式组和颜色模式组等,并通过几个实例介绍了图层混合模式在图像处理中的运用,如利用正片叠加修复曝光过度的照片,运用滤色修复曝光不足的照片等。     

Digital photo classification methodology for groups of photographers

Digital cameras have become an essential product when traveling or attending events. Because of its popularity and low cost, it is increasingly likely that more than one camera will be used at an event. The total number of photos captured is also increasing. Although the cost of digital photographs is low, managing numerous digital photos is burdensome to most users. Thus, an intelligent management tool for digital photos is required. In this paper, we propose novel clustering algorithms for concurrent digital photos obtained from multiple cameras. Since previous studies only considered a single user’s photo collection, they are not applicable to concurrent photos obtained from a group of photographers. To handle this situation, we define temporal/spatial combined clustering for the set of group photos taken from different cameras. If photos are submitted from a camera whose user has shown a preference between spatial and temporal clustering, we can obtain customized clustering output from other photo sets according to the reference clustering characteristics. We also propose unsupervised methods for general clustering output. Input concurrent photos are processed without a user’s true clusters, which can be a burden when the number of photos in the true clusters is huge. We tested our methods via more than one thousand photos taken by tourist groups. The final result was satisfactory compared to previous methods based on temporal (spatial) criteria only.     

基于聚类的彩色风景照片绘画效果生成方法

提出了一种简单实用的算法，用以对彩色照片图像处理生成类似于绘画作品的视觉效果。使用了结合颜色距离和空间位置关系的像素聚类方法来模拟画笔涂抹的区域。同当前主流图像处理软件进行的对比表明，该算法可以获得更佳的处理效果。     

Photoshop通道抠图技术在数码照片处理中的应用

本文详细介绍了Photoshop通道的工作原理,并以实例的方式介绍了通道抠图技术在数码照片处理中的应用。     

试谈用PhotoShop软件对人物进行美化处理

数码相片处理技术成为大规模普及的与IT相关的技术之一,以PhotoShop软件为例,从皮肤处理,眼睛处理,牙齿处理及形体处理3方面阐述了对人物进行美化。让人们了解PhotoShop软件的强大功能,掌握人物相片后期处理的相关操作技巧。     

基于嵌入式Linux系统数码相框的设计与实现

数码相框作为嵌入式的典型应用,比普通的相框更灵活多变。根据数码相框的需求分析开始,采用了嵌入式Linux的Libmad音频编解码技术和FrameBuffer视频编解码技术,完成了数码相框软件的设计与开发工作。最后采用C语言编写后交叉编译、移植开发、实现了数码相框。     

PhotoGeo: a photo digital library with spatial-temporal support and self-annotation

The recent popularity of digital cameras has posed a new problem: how to efficiently store and retrieve the very large number of digital photos captured and chaotically stored in multiple locations without any annotation. This paper proposes an infrastructure, called PhotoGeo, which aims at helping users with the people photo annotation, event photo annotation, storage and retrieval of personal digital photos. To achieve the desired objective, PhotoGeo uses new algorithms that make it possible to annotate photos with the key metadata to facilitate their retrieval, such as: the people who were shown in the photo (who); where it was captured (where); the date and time of capture (when); and the event that was captured. The paper concludes with a detailed evaluation of these algorithms.     

Color balancing of digital photos using simple image statistics

The great diffusion of digital cameras and the widespread use of the internet have produced a mass of digital images depicting a huge variety of subjects, generally acquired by unknown imaging systems under unknown lighting conditions. This makes color balancing, recovery of the color characteristics of the original scene, increasingly difficult. In this paper, we describe a method for detecting and removing a color cast (i.e. a superimposed color due to lighting conditions, or to the characteristics of the capturing device), from a digital photo without any a priori knowledge of its semantic content. First a cast detector, using simple image statistics, classifies the input images as presenting no cast, evident cast, ambiguous cast, a predominant color that must be preserved (such as in underwater images or single color close-ups) or as unclassifiable. A cast remover, a modified version of the white balance algorithm, is then applied in cases of evident or ambiguous cast. The method we propose has been tested with positive results on a data set of some 750 photos.