1. Field of the Invention
The present invention relates to digital displays. More particularly, the present invention relates to a system and a method providing a Bit-Depth Extension (BDE) technique for preventing contouring artifacts in an image displayed by a display having a bit-depth that is less than the bit-depth of the image.
2. Description of the Related Art
Continuous tone, or contone, imagery typically has as a minimum bit depth of 24 bits, of which eight bits are allocated for each of the red (R), green (G) and blue (B) colors in a display. The term “bit depth,” as used herein, means the number of bits of resolution per pixel. Lower cost displays, however, have bit-depth limitations based on the amount of Video Random Access Memory (VRAM) that is available, the characteristics of the display, and/or the digital-to-analog converters (DAC) that are used in some cathode ray tube (CRT) displays.
For example, at one time the highest gray-level resolution for typical laptop computers is typically the “thousands of colors” mode, which corresponds to a bit depth of 16 bits. The 16-bit bit depth is typically allocated as five bits for red, six bits for green and five bits for blue. In contrast, desktop-type computers or laptop computers having more VRAM typically have a bit depth of 24 bits in which eight bits are allocated for each of the red, green and blue colors. As another example, other lower quality display devices have only a 15-bit bit depth, which is allocated as five bits per color.
Contour artifacts appear in smooth gradient regions of an image displayed by a display having a bit depth that is less than the bit depth of the image. For example, a 24-bit bit-depth image that includes part of the sky will exhibit visible contour lines in the smooth gradient regions of the sky when the image is displayed on a display having a bit depth that is less than 24 bits. Techniques have been developed for reducing contour artifacts. In particular, L. G. Roberts performed some of the original work in the area of contour prevention for pulse code modulation (PCM) coded and transmitted images. See, for example, L. G. Roberts, “Picture coding using pseudo-random noise,” IRE Transactions on Information Theory, pp. 145-154, February 1962. The Roberts technique, commonly referred to as the Roberts' noise modulation technique, is principally an image-compression technique based on a gray-level resolution reduction using amplitude quantization. An image having a bit depth of seven bits can be compressed using the Roberts' noise modulation technique to become an image having a bit depth of two to three bits.
U.S. Pat. No. 3,244,808 to Roberts discloses a conventional system utilizing the Roberts' noise modulation technique. FIG. 1 depicts a functional block diagram 100 of the general approach of a conventional Roberts' noise modulation technique. In FIG. 1, a contone image 101, which for this example has a six-bit bit depth, is combined in a summer 102 with a one-dimensional (1-D) white-noise sequence that is generated by a pseudo-random noise generator 103. The noise signal output from pseudo-random noise generator 103 has a zero mean and, consequently, prevents a tonescale shift and minimizes clipping in the output of summer 102.
The noise is added to contone image 101 during the raster scan prior to being quantized by quantizer 104, Pulse Code Modulated (PCM) encoded, and transmitted at functional block 105. The rasterization turns the added noise from a 1-D white noise to a two-dimensional (2-D) white noise. After receiver 106 receives the quantized contone image with the added noise, the image is PCM decoded. In order that the addition of the pseudo-random noise does not cause degradation of the image quality, the noise is subtracted at 107 prior to being displayed on display 108. The subtracted noise must be synchronized with the added noise so that the subtracted noise is identical and in-phase with the transmitted noise.
While the Roberts' noise modulation technique tends to break up contours that appear in a displayed image having a limited bit-depth, Roberts' noise modulation technique was largely ignored as a technique for reducing contour artifacts because the technique was developed as a compression technique and because at the time the Roberts' compression technique was developed, breaking up of contouring artifacts was an empirical observation. Interestingly, the primary distortion associated with the Roberts' noise modulation technique appears as contour artifacts that are often manifested as false edges in slowly varying gradients. It has since come to be understood that varying the orientation of elements along the contour by adding noise breaks up contouring artifacts so that the elements fall outside the association field for the Human Visual System (HVS). Other techniques of compression, such as digital pulse code modulation (DPCM) and discrete cosine transform (DCT), have enabled greater degrees of compression without contouring artifacts by primarily shifting the compression process from the spatial domain to the frequency domain.
U.S. Pat. No. 3,739,082 to Lippel discloses another conventional system in which an ordered-pattern noise is added to a contone image, similar to the Roberts' compression technique, but differs in that the added noise is not removed at the receiver. FIG. 2 depicts a functional block diagram 200 of a system according to Lippel. In FIG. 2, a contone image 201 is summed at 202 with a pseudo-random noise 203 before being transmitted to a display device 204. Display device 204 includes a quantizer 205 that is needed based on the limitations and costs of the display driver for display 206. While the Lippel approach is simpler than the approach of Roberts, the overall results are not as good because subtraction of the noise has been omitted at the receiver. Nevertheless, the Lippel approach allows noise to be applied to hardcopy quantization limitations, as opposed to limitations appearing based on compression, as in Robert's noise modulation technique.
The techniques disclosed by U.S. Pat. No. 3,244,808 to Roberts and U.S. Pat. No. 3,739,082 to Lippel are commonly referred to as microdithering techniques in order to differentiate the technique from dithering techniques, which more commonly refers to halftoning techniques. A microdithering technique is based on an amplitude-dithering or a dithering-pattern addition technique, while a halftoning dithering technique is based on a spatial dither. Microdithering techniques generally can be classified into one of two categories; either as (1) a general dithering approach that adds noise, or (2) as an approach that is specifically directed to eliminating contour artifacts. (A third type of dithering, referred to as phase dithering, is used within the computer graphics field for an image is essentially continuous and must be sampled for display. Because computer graphics do not need a camera and there are no associated sensor geometry limitations, the image can be sampled in a spatially varying manner.)
The noise conventionally used for microdithering techniques is a uniform Probability-Density-Function (PDF) white noise having an amplitude that is equal to one-half of the quantization interval of the reduced quantization levels stage. The amplitude of the PDF white noise was derived from further analysis by J. Thompson et al., as disclosed in “A pseudo-random quantizer for television signals,” Proceedings of the IEEE, vol. 55 no. 3, pp. 353-355, 1967. One way of looking at microdithering is that addition of a noise acts to move the quantizing intervals around from pixel to pixel, thereby breaking up contours.
Several approaches have been developed that take advantage of the low-pass filter (LPF) characteristics of the Human Visual System (HVS) and, consequently, select a pseudo-random noise having a high-pass characteristic. Any added noise appearing on the display would be attenuated by the LPF characteristics of the HVS, which is primarily based on optical properties. See, for example, R. Ulichney, “Dithering with Blue Noise,” Proceedings of the IEEE, vol. 76, no. 1, pp. 56-79, 1988, and T. Mitsa et al., “Digital halftoning using a Blue Noise Mask,” In SPIE Electronic Imaging Conference, V. 1452, pp. 45-56, 1991. The noises selected by Ulichney and by Mitsa et al. are based on a general understanding of the HVS and are similar to dithering noises that are used for hardcopy haftoning applications. The spectrally shaped noises used by Ulichney and Mitsa et al. are termed “blue noise” as an analogy to the term “pink noise,” which is used in audio application. The color term “blue” for the noise comes from the spectral shape of the noise as a function of frequency. FIG. 3 depicts an exemplary spectrum 300 of a blue noise. Spectrum 300 generally has a shape corresponding to high frequencies and peaks at peak frequency fg, hence the term “blue”. Peak frequency fg depends on the gray level g (normalized to 0-1) and ranges from 0 to 0.7 cy/pixel.
Microdithering techniques can be conceptually extended to displays by removing the compression stage and basing the transmitter stage noise on the inherent noise of the display. Accordingly, the noise associated with the display must be known and/or can be measured based on a fixed-pattern component of the noise of displays. U.S. Pat. No. 6,441,867 B1 to Daly discloses a conventional microdithering technique that uses the inherent noise of a display and that can be classified as a general noise-additive dithering technique. FIG. 4 depicts a functional block diagram 400 illustrating one microdithering technique disclosed by Daly that uses the inherent noise of a display. In FIG. 4, a contone image 401 is summed at 402 with a dithering pattern 403 that is based on a fixed-pattern display noise 404. Fixed-pattern display noise 404 is used to shape, or filter, a pseudo-random noise 409 to create dithering pattern 403. Fixed-pattern display noise 404 is measured from a display 405 of a display device 406. A quantizer 407 is not required for compression, but is needed based on the limits and costs of the display driver for display 405. Note that the signs of the noise are reversed in contrast to FIG. 1. That is, the noise is added at display 405 (by display 405), and subtracted prior to quantizer 407, which is trivial when the noise has a zero mean. Accordingly, the pre- and post-quantization noise essentially cancel (except for any quantization error), thereby reducing contouring artifacts, particularly when going from 256 to 64 levels (i.e., a bit depth of 8 bits to a bit depth of 6 bits). Nevertheless, the inability to subtract the added noise results in an image that has visible noise.
For each of the conventional microdithering techniques depicted in FIGS. 1, 2 and 4, the goal is to add as much noise to the contone image as possible, while making sure that the added noise is not visible in the displayed image. Because the noise is not cancelled in the conventional approaches shown in FIGS. 2 and 4, the smallness of the size of the quantization levels are limited to avoid the noise being visible. That is, the quantization levels must be sufficient large to avoid the noise from becoming visible.
FIG. 5 depicts a functional block diagram 500 illustrating another microdithering technique disclosed by U.S. Pat. No. 6,441,867 B1 to Daly for preventing contouring artifacts in an image displayed by a display having a bit-depth that is less than the bit-depth of the image. According to this aspect of Daly, a dithering pattern is used that is based a visual model of the equivalent input noise of the HVS instead of a dithering pattern that is based on the noise of the display. The equivalent input noise of the HVS is generated based on the frequency response of the HVS, which is measured by an observer visual system 507 and modeled as an Equivalent Input Noise Visual Model 508. Because the CSF can be modeled as anisotropic in 2-D, the noise also has anisotropic statistics. Thus, a frequency-domain technique is used to model the noise. Equivalent Input Noise Visual Model 508 is used at 510 to shape, or filter, pseudo-random noise 509 to create dithering pattern 503. A contone image 501 is combined by a summer 502 with dithering pattern 503 before being input to a display device 504. Display device 504 includes a quantizer 505 that is required based on the limitations and costs of the display driver for display 506.
The approach used by Daly in FIG. 5 is similar to a characterization of an electronic component by referring the internal noise of the component to its equivalent effect as if the noise was an input noise. That is, the internal noise of the component is described in units of the input. While a visual noise may exist in units of millivolts of a neuronal cell charge, once the visual noise has been referred to as an input noise, the noise is in units of contrast (e.g., RMS contrast). The equivalent input noise of the HVS is often modeled as the inverse of the frequency response of the HVS, termed the Contrast Sensitivity Function (CSF).
While FIG. 5 depicts dithering pattern 503 being added to contone image 501, dithering pattern 503 could alternatively be used to multiply contone image 501 depending on how the nonlinear domain of the code values of the image are represented. That is, adding in a log scale is equivalent to a multiplication in a linear scale. Adding in a gamma-corrected domain is a rough approximation to either log or linear addition.
FIG. 6 depicts a functional block diagram 600 illustrating a microdithering technique disclosed by U.S. Pat. No. 6,441,867 B1 to Daly for preventing contouring artifacts in a color image displayed by a display having a bit-depth that is less than the bit-depth of the image. According to this aspect of Daly, a Chromatic Equivalent Noise Model 608 is generated from the observer visual system 607. Chromatic Equivalent Noise Model 608 converted to the RGB space by a Visual Chroma-to-RGB Space Converter 611 for separation into an equivalent noise model for each color image plane. Each respective equivalent noise model is used at 610a-610c to shape a pseudo-random noise 609a-609c to generate dithering patterns 603a-603c. A dithering pattern 603a-603c for each color image plane is then added to the corresponding color plane of the contone image 601a-601c by summers 602a-602c, respectively. Display device 604 includes quantizers 605a-605c that are required based on the limitations and costs of the display driver for display 606.
Spatial dithering techniques used for preventing contouring artifacts typically reduce the spatial resolution of the image. Consequently, what is needed is a technique for eliminating or reducing the contouring artifacts that is computationally simple and does not reduce the spatial resolution of the image.