Abstract:
An image acquisition system has a computer and one or more imaging devices coupled to the computer. Each imaging device has a device memory and is capable of capturing a digital image and storing the image in its memory. An image device manager is implemented in software on the computer to control operation of the imaging devices. The image device manager presents a user interface (UI) within the familiar graphical windowing environment. The UI has a context space that pertains to a particular imaging context (e.g., scanning, photography, and video). The UI also has a persistently-visible imaging menu positioned within the context space that lists options particular to the imaging context. For example, if the context space pertains to the digital camera context, the menu lists options to take a picture, store the image on the computer, send the image in an email, and so on. In the scanner context, the menu lists options to select an image type, preview an image, send the image to a particular destination, and scan the image. The image acquisition system also includes a set of application program interfaces (APIs) that expose image management functionality to applications. The APIs enable applications to manage loading and unloading of imaging devices, monitor device events, query device information properties, create device objects, capture images using the devices, and store or manipulate the images after their capture.
Abstract:
Techniques and tools for analyzing and adjusting the exposure of digital images are described. For example, a computer processes a digital image by analyzing exposure data, assigning an image classification (e.g., StretchNeeded, UnderExposed, OverExposed, or Normal) based on the analysis, and selecting an exposure compensation technique (e.g., histogram stretch, positive gamma curve, negative gamma curve, or no adjustment) based on the image classification. The exposure data can be luminance values for pixels in the digital image represented in a histogram. The computer can produce transform data comprising a transformation of the exposure data according to the selected exposure compensation technique. The computer can store transform data in a look-up table and can store the look-up table in the digital image file. The described techniques and tools can be implemented as a feature of an operating system environment and can be activated responsive to user action via a user interface.
Abstract:
Techniques and tools for automatically analyzing and adjusting digital images upon acquisition are described. In one aspect, an application analyzes and adjusts image data (e.g., pixel data) automatically upon acquiring (e.g., from a source such as a digital camera) a digital image. Adjustments can be based on, for example, image orientation, red-eye detection, blurriness, color balance, exposure, or noise detection. Metadata corresponding to image adjustments can be stored in an adjusted image file to preserve the original image. In another aspect, a computer system comprises image analysis and image adjustment software modules for analyzing and adjusting digital image data at image acquisition time. The image adjustment module can include one or more processing filters. A customizable software architecture allows customization of the image adjustment software module (e.g., by adding, removing or reordering processing filters). The described techniques and tools can be implemented as features of an operating system environment.