Intelligent Image Processing and Signal Processing for wearable computing and AR (augmediated reality)

随着无处不在的移动的/便携式成像和计算现在成为现实，以及可穿戴计算（例如数字眼镜）刚刚成为现实，我们正在进入一个时代，在这个时代中，我们的日常生活正在或即将由基于视觉的计算机介导。 我们中的许多人大部分时间都带着相机和计算设备（智能手机或照相手机）。这些设备将很快以数字眼镜的形式出现，以帮助我们中的许多人看得更清楚，并提高我们的生活质量。这项技术将特别受到越来越多的视力下降的老年人的欢迎。 此外，随着技术变得更加个性化，数字眼镜将帮助我们记住姓名和面孔（例如可穿戴面部识别器），找到我们的方式（数字地图覆盖增强介导现实），并为我们提供更好的安全性（例如个人安全），健康（传感等）。和幸福 从我长期的个人经验来看（从我童年开始，我发明、设计、建造和试验可穿戴计算和数字眼镜超过35年--首先是年轻时的业余科学家，后来是我的职业生涯），我帮助这个行业发展。 许多行业都在解决直接的商业利益，但需要研究智能图像处理的基础方面，特别是与个人成像设备（小型便携式或可穿戴相机系统）相关的方面。 特别是，仍然存在的一个核心问题是让相机像人眼一样“看”。相机的空间分辨率已经从数千像素增加到百万像素，但是每个像素的图像质量（例如动态范围）没有跟上。 第一台数码相机于1975年发明（由柯达的Steven Sasson发明），具有10，000像素（基于费尔柴尔德100*100像素传感器），每通道每像素4位（1通道，即灰度）。 如今，移动的和便携式照相手机的像素高达4100万像素（例如，诺基亚PureView 808），并且一些照相机处于千兆像素范围内，即空间分辨率是1975年的10万倍以上。因此，许多相机可以“看到”细节（例如“阅读”报纸上的小字）比当时好几千倍。 但它们仍然无法在动态范围上与人眼相匹配（即能够同时感知弱光和真正明亮的光线）。 值得注意的是，现代相机的位深度通常只有38年前世界上第一台数码相机的两倍（8位与4位相比）。 最近，我通过发明并稳步改进HDR（高动态范围）成像来解决这个问题。 Robertson等人写道：

With ubiquitous mobile/portable imaging and computing now a reality, and wearable computing (e.g. Digital Eye Glass) just becoming a reality, we are entering an era in which our everyday lives are being or will soon be mediated by vision-based computers. Many of us already carry a camera and computing device (smartphone or cameraphone) most of the time. These devices will soon take the form of Digital Eye Glass to help many of us see better, and improve the quality of our lives. This technology will be especially welcome to the growing population of older individuals with failing eyesight. Moreover, as technologies become more personal, the Digital Eye Glass will help us remember names and faces (e.g. the wearable face recognizer), find our way (digital maps overlayed with Augmediated Reality), and provide us with improved safety (e.g. personal security), health (sensing, etc.) and well-being. From my long-standing personal experience (more than 35 years of inventing, designing, building, and experimenting with wearable computing and Digital Eye Glass since my childhood -- first as an amateur scientist in my youth, and later in my professional life), I have helped this industry evolve. Much of the industry is addressing immediate business interests, but there is a need for research on the foundational aspects of Intelligent Image Processing specifically related to personal imaging devices (small portable or wearable camera systems). In particular, a core issue that remains is getting cameras to "see" as well as the human eye does. Already the spatial resolution of cameras has increased from thousands of pixels to megapixels, but image quality (e.g. dynamic range) at each pixel has not kept pace. The first digital camera was invented (by Steven Sasson of Kodak) in 1975, and had 10,000 pixels (based on a Fairchild 100*100 pixel sensor), and 4 bits-per pixel per channel (1 channel, i.e. greyscale). Today, mobile and portable camera phones are up to 41 Megapixels (e.g. Nokia PureView 808), and some cameras are in the gigapixel range, i.e. spatial resolutions that are more than 100,000 times what they were in 1975. Thus many cameras can "see" the detail (e.g. "read" small print on a newspaper) thousands of times better now than then. But they still cannot match the human eye for dynamic range (i.e. being able to simultaneously sense in low-light and really bright light). Remarkably, the bit depth of modern cameras is typically only twice what the world's first digital camera was 38 years ago (8 bits compared to 4 bits). Recently I have addressed this problem by inventing and steadily improving something called HDR (High Dynamic Range) Imaging. Robertson et al. write: