Among images that are captured using conventional or digital cameras, as well as other conventional imaging devices, such as medical imaging devices, there are pictures that fall below customer requirements for an acceptable quality level. For example, it has been found that among all color negative frames of film that are submitted to photofinishers, there are some negatives that produce, when printed, very poor quality prints.
Depending on the local salability policies and agreements with customers around quality standards specifications, such images frequently cannot be sold to the customers. There usually are several categories of such prints. For example, one category is referred to as a “dud” category, comprising mainly blank images, severely underexposed or overexposed images, and images of extremely poor focus. Other categories may include images where the main subject is not properly positioned, such as when a person's head is cut off and/or eyes are not visible, or where the images are only moderately unsharp or noisy but nonetheless unacceptable. Additionally, some images captured with a digital camera may have very poor sharpness, which may not be easily detectable by a user observing the image, e.g., on a preview screen on the camera, prior to submitting the images for printing. Also, certain medical images suffer from low sharpness and other problems, such as noise, and cannot be used by a radiologist for a medical examination. In that case, it would be advantageous to identify the problem in a timely fashion so that the image can be re-taken, in a manner conveniently for the patient.
In all described examples, detecting images with unacceptable sharpness levels is a useful operation that can result in cost and time saving benefits.
Current methods for detecting unacceptable images primarily rely on visual inspection of each photograph. Identifying those images automatically will provide a cost benefit to phototinishers as well as users who print their images at home or via an on-line service.
In U.S. Pat. No. 6,028,676, entitled “Output Method and Apparatus for Estimating Image Quality Prior to Output” and issued in the name of Nakao on Feb. 22, 2000, the disclosed method deals with the problem of data transfer from a host computer to a printer, where the quantity of image data is substantial and the printer may have insufficient memory to store all the data. The method therefore sets out to estimate the resultant effect on image quality before the print data is transferred to the printer. In this case, the file size can be an indicator of a potential problem, e.g., whether an initial high-resolution image, if printed, would have inferior quality. Based on such estimation, an output apparatus and method determines in advance whether to transfer the data for printing, print the data or provide a display to an operator indicating that an output image will be of inferior quality. The method thus intends to account for the memory limitations of the printing device, which can have adverse effects on the output image quality. Consequently, while it is assumed that the limitations of the printing process may preclude an input image from being output with sufficient quality, the disclosed method is not suitable for differentiating the images in terms of their original quality. Hence, it cannot be used to prevent potentially wasteful images from being printed, as potentially wasteful images of low original quality will still be printed if printer memory is sufficient.
U.S. Pat. No. 6,018,397, entitled “Digital Image Processing with Indication to User of Hardcopy Output Image Quality” and issued in the names of Cloutier and Wheeler on Jan. 25, 2000, discloses a method for establishing a boundary level of acceptable hardcopy print quality level. This method involves determining quality based on selected image print size and printing magnification and provides a warning to the user prior to generation of the hardcopy print that alerts the user when the determined print image quality will be unsatisfactory. Similar to the aforementioned U.S. Pat. No. 6,028,676 described above, this method is not intended to predict an output print acceptability based on the variable quality of an input image, but rather, assumes a high level of input quality and considers the user-selected magnification level and desirable image size as factors that may lead to unsatisfactory print quality.
In U.S. Pat. No. 5,694,484, entitled “System and Method for Automatically Processing Image Data to Provide Images of Optimal Perceptual Quality” and issued in the names of Cottrell et al. on Dec. 2, 1997, an image processing system automatically optimizes the perceptual quality of images undergoing a series of selected image-processing operations. The system takes into consideration profiles of sources from which the images are generated, profiles of intended applications, and the impact that image processing operations (individually or in concert) will have on perceived image quality. The described system uses a body of relationships linking human perception of image quality with objective metrics (such as sharpness, grain, tone and color) to vary a collection of adjustable parameters in the requested image-processing operations in order to automatically maximize image quality for resulting pictures. By controlling a collection of parameters in the requested image processing operations, it works automatically to maximize subjective quality for the resulting picture. However, although input images are optimized during the processing phase for their quality, the disclosed system does not assess the original input quality against agreed upon standards of acceptability to determine whether the original should be treated differently at the stage of output, that is, whether the original is even worthy of processing and output as a print in the first place.
In commonly assigned U.S. Pat. No. 6,535,636, entitled “A Method for Automatically Detecting Digital Images that are Undesirable for Placing in Albums” and issued in the names of Savakis and Loui on Mar. 18, 2003, and which is incorporated herein by reference, a method is disclosed for automatically classifying a digital image as a dud (or a wasteful image). This method is based on computational assessment of several image properties, including the sharpness, contrast, noise, and exposure of digital images, either individually or in combination. For the contrast-related assessment, a measure of a standard deviation of the intensity histogram extracted from the edge profile is used, while for the noise-related assessment, a standard deviation of pixels from a part of the image is used. With respect to sharpness-related assessment, the method includes obtaining an edge profile of the image, computing a histogram from the edge profile, locating predetermined edges of the edge histogram, and computing a centroid of gradients of the predetermined edges to determine a mean value of the edge gradient. Dud images due to unacceptable sharpness are therefore identified using a measure of the edge strength. One might anticipate however, that there are images with somewhat weak edges that can still be acceptable, such as scenes with water and sky, or images that are not extensively blurred. Conversely, there are images with strong edges in one local area, which still possess very low quality if the rest of the image is grossly unsharp, especially where the primary subject is unsharp. In these cases, the suggested measure may not perform very well. Another shortcoming of the disclosed method is the necessity to apply different measures, such as contrast or underexposure estimation, when the edge degradation occurs as a secondary problem because of severe under- or over-exposure. In these cases, observers may perceive the edges as blurry and report them as such; however, the sharpness measure in terms of the edge gradient estimation is not sufficient to determine the acceptability of the image.
Consequently, a need exists to develop a more reliable method for automatic determination of the acceptability of digital images, especially those which are submitted for printing, and in particular because of a problem with sharpness.
USPTO Backgrounds
USPTO Backgrounds