- Image Quality
Image Quality is a characteristic of an image that measures the perceived image degradation (typically, compared to an ideal or perfect image). Imaging systems may introduce some amounts of distortion or artifacts in the signal, so the quality assessment is an important problem.
Image Quality Assessment Categories
There are several techniques and metrics that can be measured objectively and automatically evaluated by a computer program. Therefore, they can be classified as Full Reference Methods (FR) and No-Reference Methods (NR). In FR image quality assessment methods, the quality of a test image is evaluated by comparing it with a reference image that is assumed to have perfect quality. NR metrics try to assess the quality of an image without any reference to the original one.
Image Quality Factors
* Sharpness - determines the amount of detail an image can convey. System sharpness is affected by the lens (design and manufacturing quality, focal length, aperture, and distance from the image center) and sensor (pixel count and anti-aliasing filter). In the field, sharpness is affected by camera shake (a good tripod can be helpful), focus accuracy, and atmospheric disturbances (thermal effects and aerosols). Lost sharpness can be restored by sharpening, but sharpening has limits. Oversharpening, can degrade image quality by causing "halos" to appear near contrast boundaries. Images from many compact digital cameras are oversharpened.
Noiseis a random variation of image density, visible as grain in film and pixel level variations in digital images. It arises from the effects of basic physics— the photon nature of light and the thermal energy of heat— inside image sensors. Typical noise reduction (NR) software reduces the visibility of noise by smoothing the image, excluding areas near contrast boundaries. This technique works well, but it can obscure fine, low contrast detail.
Dynamic range- Dynamic range (or exposure range) is the range of light levels a camera can capture, usually measured in f-stops, EV (exposure value), or zones (all factors of two in exposure). It is closely related to noise: high noise implies low dynamic range.
Tonal Response— the relationship between light and pixel level.
Contrast- also known as gamma, is the slope of the tonal response curve. High contrast usually involves loss of dynamic range— loss of detail, or clipping, in highlights or shadows— when the image is displayed.
Color accuracy- is an important but ambiguous image quality factor. Many viewers prefer enhanced color saturation; the most accurate color isn't necessarily the most pleasing. Nevertheless it is important to measure a camera's color response: its color shifts, saturation, and the effectiveness if its white balance algorithms.
Distortion- is an aberration that causes straight lines to curve near the edges of images. It can be troublesome for architectural photography and metrology (photographic applications involving measurement). Distortion is worst in wide angle, telephoto, and zoom lenses. It often worse for close-up images than for images at a distance. It can be easily corrected in software.
Light falloff- Also known as vignetting, darkens images near the corners. It can be significant with wide angle lenses.
Exposure accuracy- You can usually determine it quickly with the help of the histogram, to alter the accuracy you can change the exposure compensation or the way you meter. Exposure accuracy can be an issue with fully automatic cameras and with video cameras where there is little or no opportunity for post-exposure tonal adjustment. Some even have exposure memory: exposure may change after very bright or dark objects appear in a scene.
Lateral chromatic aberration- (LCA), also called "color fringing" is a lens aberration that causes colors to focus at different distances from the image center. It is most visible near corners of images. LCA is worst with asymmetrical lenses, including ultrawides, true telephotos and zooms. It is strongly affected by demosaicing.
Veiling glare- is stray light in lenses and optical systems caused by reflections between lens elements and the inside barrel of the lens. It predicts the severity of lens flare, image fogging (loss of shadow detail and color) as well as "ghost" images that can occur in the presence of bright light sources in or near the field of view.
Color moiré- is artificial color banding that can appear in images with repetitive patterns of high spatial frequencies, like fabrics or picket fences. It is affected by lens sharpness, the anti-aliasing (lowpass) filter (which softens the image), and demosaicingsoftware. It tends to be worst with the sharpest lenses.
Artifacts- Software (especially operations performed during RAW conversion) can cause significant visual artifacts, including Data compression and transmission losses (e.g. Low quality JPEG), oversharpening "halos" and loss of fine, low-contrast detail.
* Sheikh, H.R.; Bovik A.C., Information Theoretic Approaces to Image Quality Assessment. In: Bovik, A.C. Handbook of Image and Video Processing. Elsevier, 2005.
Subjective video quality
Mean Squared Error(MSE)
Universal Image Quality Index
* [http://www.imatest.com/docs/iqf.html Image Quality Factors] from [http://www.imatest.com Imatest]
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