Image analysis – Image enhancement or restoration – Variable threshold – gain – or slice level
Reexamination Certificate
2001-07-27
2004-09-14
Patel, Kanji (Department: 2625)
Image analysis
Image enhancement or restoration
Variable threshold, gain, or slice level
C345S589000, C358S521000
Reexamination Certificate
active
06792160
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates to the enhancement of digital images. More particularly, this disclosure provides a system and method of rendering image detail to optimize visual perception using a tone-augmentation algorithm.
BACKGROUND OF THE INVENTION
Typically, digital tone correction is applied globally over all pixel values in a digital image in order to enhance the visual appearance of the image in the sense that all pixels of a given value are mapped to the same new value. In this type of technique a single “so-called” tone curve or mapping is defined and all pixel values in the image are adjusted according to this tone curve. As a result, for each input value there is a corresponding output value. The problem with this type of global adjustment is that different areas within the image may need different types of tone adjustment, which, depending on the dynamic range and contrast of the image, will in turn depend on the local values of neighboring pixels. Consequently, a global tone adjustment technique will often enhance some regions within the image while having no visual affect or having an adverse visual affect on other regions.
As a result, local adaptive tone correction techniques have been investigated. In general, a local tone correction operation will map one input value to potentially different output values depending on the values of the neighboring pixels. This, for example, allows for simultaneous shadow and highlight adjustments, without one being to the detriment of the other.
Prior art local-tone correction techniques include manual operations for evening out image illumination by manual adjustment of image parameters. For instance, the analog darkroom techniques known as dodging and burning require a user to physically specify or identify regions of the image to be lightened or darkened. Dodging and burning consists essentially of defining and positioning physical masks during the analog exposure of a print. In the digital case, these techniques can also be carried out using a mouse or other computer interface to select specific pixels or regions in an image to be lightened or darkened. In addition to manually identifying regions for adjustment, the user must also control the amount of adjustment. The problem with this technique is that it requires a certain level of skill and a large amount of time and effort to achieve.
Another known solution is based on edge-ratio preserving algorithms. These algorithms use an iterative processing of an image in order to determine a corrected output image. This iterative process consists of taking ratios of a number of neighboring pixel values, multiplying these ratios and finally, resetting these ratios if some maximum value is achieved. In this way image edge lightness values may be reproduced in a more visually optimized manner. The assumption is that this sequence of calculations mimics the human visual system. Specifically, an observer is constantly scanning an image or scene and is presumed to be performing some type of normalization relative to the scene or image white point. The algorithms attempt to model the human visual system and reconstruct a digitally captured image with perceptually correct local color correction from a given scene. Given a calibrated input, this approach generates images that are similar to those that might be produced using the manual technique, (where a calibrated input is an image that accurately represents some physical quantity that can be directly measured, such as radiance or luminance). However, current implementations tend to be computationally intensive. In addition, there is no simple framework to allow an interactive or user specified control over these algorithms particularly when correcting uncalibrated inputs images or under, over and unevenly exposed images.
Other approaches include histogram equalization, image segmentation, or specialized hardware. Histogram equalization techniques use properties of the statistical distribution of the lightness values in the image to derive a tone correction curve for that image. Image segmentation techniques attempt to automatically partition images into specific areas of the image. These areas are then lightened or darkened based on an analysis of these areas. Hardware such as logarithmic CCD sensors and dual sampling CMOS sensors provide a better means of capturing high dynamic range scene data. However, this hardware does not specify how this high dynamic range data should be processed or mapped to a lower dynamic range devices.
The problem with all of these known techniques is that they are either computationally intensive, difficult to implement or use, are specific to a particular type of image problem, and/or are often associated with the introduction of significant artifacts.
What is needed is a low computational general purpose tone correction solution which simplifies tone adjustment/correction for the non-skilled user so as to obtain visually desirable results when correcting a wide variety of images including very high-contrast, high-dynamic range images to images lacking contrast throughout the entire dynamic range.
SUMMARY OF THE INVENTION
The present invention is an effective, intuitively simple, low computational system and method of tone correction of most types of digital images, and in particular, images of high-dynamic range. In accordance with the method, the digital image, having a plurality of pixel values, is filtered on a pixel-by-pixel basis to obtain a corresponding locally averaged value for each pixel value. Each pixel's locally averaged value is then used to obtain shadow and highlight values from selected shadow and highlight functions, respectively. At least one tone function is derived from one of the shadow and highlight values and each image pixel is then remapped according to the derived tone function to generate a remapped pixel value.
In another embodiment, the shadow value corresponding to each pixel value is used to derive a first shadow-based tone function and the highlight value is used to derive a second highlight-based tone function. Each pixel value of the image is then remapped using the first tone function to obtain an intermediate pixel value, and then each intermediate pixel value is remapped using the second tone function to obtain a final tone adjusted pixel value.
In one embodiment, function parameters of the selected highlight and shadow functions can be varied within the dynamic range of the image data to obtain adjusted shadow and highlight values. Adjusted tone functions are then derived using the adjusted shadow and highlight values and the image pixel values can be reiteratively remapped according to the method as described above using the adjusted tone functions.
The system of the present invention for tone correction of a digital image includes a preliminary image convolution n filter for generating a corresponding locally averaged pixel value for each of the plurality of pixel values in the image. A means embodying the selected highlight and shadow functions provides a corresponding highlight value and a corresponding shadow value in response to each of the locally averaged pixel values. A tone function derivator derives at least one tone function in response to the corresponding highlight and shadow values. Each pixel value is remapped by a remapper according to the at least one derived tone function to obtain a tone adjusted pixel value.
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Atsuhisa Saito et al: “Optimum Contrast Enhancement Using Fuzzy Sets” Systems and Computers in Japan, Scripta Technica Journals, NY, US vol. 22, No. 11, 1
McGuire Michael D.
Shaw Rodney
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