2,930 research outputs found
Colour constancy using von Kries transformations: colour constancy "goes to the Lab"
Colour constancy algorithms aim at correcting colour towards a correct perception within
scenes. To achieve this goal they estimate a white point (the illuminant's colour), and correct
the scene for its in uence. In contrast, colour management performs on input images colour
transformations according to a pre-established input pro le (ICC pro le) for the given con-
stellation of input device (camera) and conditions (illumination situation). The latter case
presents a much more analytic approach (it is not based on an estimation), and is based on
solid colour science and current industry best practises, but it is rather in exible towards cases
with altered conditions or capturing devices. The idea as outlined in this paper is to take up
the idea of working on visually linearised and device independent CIE colour spaces as used
in colour management, and to try to apply them in the eld of colour constancy. For this
purpose two of the most well known colour constancy algorithms White Patch Retinex and
Grey World Assumption have been ported to also work on colours in the CIE LAB colour
space. Barnard's popular benchmarking set of imagery was corrected with the original imple-
mentations as a reference and the modi ed algorithms. The results appeared to be promising,
but they also revealed strengths and weaknesses
Design of Novel Algorithm and Architecture for Gaussian Based Color Image Enhancement System for Real Time Applications
This paper presents the development of a new algorithm for Gaussian based
color image enhancement system. The algorithm has been designed into
architecture suitable for FPGA/ASIC implementation. The color image enhancement
is achieved by first convolving an original image with a Gaussian kernel since
Gaussian distribution is a point spread function which smoothen the image.
Further, logarithm-domain processing and gain/offset corrections are employed
in order to enhance and translate pixels into the display range of 0 to 255.
The proposed algorithm not only provides better dynamic range compression and
color rendition effect but also achieves color constancy in an image. The
design exploits high degrees of pipelining and parallel processing to achieve
real time performance. The design has been realized by RTL compliant Verilog
coding and fits into a single FPGA with a gate count utilization of 321,804.
The proposed method is implemented using Xilinx Virtex-II Pro XC2VP40-7FF1148
FPGA device and is capable of processing high resolution color motion pictures
of sizes of up to 1600x1200 pixels at the real time video rate of 116 frames
per second. This shows that the proposed design would work for not only still
images but also for high resolution video sequences.Comment: 15 pages, 15 figure
Wavelet-Based Enhancement Technique for Visibility Improvement of Digital Images
Image enhancement techniques for visibility improvement of color digital images based on wavelet transform domain are investigated in this dissertation research.
In this research, a novel, fast and robust wavelet-based dynamic range compression and local contrast enhancement (WDRC) algorithm to improve the visibility of digital images captured under non-uniform lighting conditions has been developed. A wavelet transform is mainly used for dimensionality reduction such that a dynamic range compression with local contrast enhancement algorithm is applied only to the approximation coefficients which are obtained by low-pass filtering and down-sampling the original intensity image. The normalized approximation coefficients are transformed using a hyperbolic sine curve and the contrast enhancement is realized by tuning the magnitude of the each coefficient with respect to surrounding coefficients. The transformed coefficients are then de-normalized to their original range. The detail coefficients are also modified to prevent edge deformation. The inverse wavelet transform is carried out resulting in a lower dynamic range and contrast enhanced intensity image. A color restoration process based on the relationship between spectral bands and the luminance of the original image is applied to convert the enhanced intensity image back to a color image. Although the colors of the enhanced images produced by the proposed algorithm are consistent with the colors of the original image, the proposed algorithm fails to produce color constant results for some pathological scenes that have very strong spectral characteristics in a single band. The linear color restoration process is the main reason for this drawback. Hence, a different approach is required for tackling the color constancy problem. The illuminant is modeled having an effect on the image histogram as a linear shift and adjust the image histogram to discount the illuminant. The WDRC algorithm is then applied with a slight modification, i.e. instead of using a linear color restoration, a non-linear color restoration process employing the spectral context relationships of the original image is applied. The proposed technique solves the color constancy issue and the overall enhancement algorithm provides attractive results improving visibility even for scenes with near-zero visibility conditions.
In this research, a new wavelet-based image interpolation technique that can be used for improving the visibility of tiny features in an image is presented. In wavelet domain interpolation techniques, the input image is usually treated as the low-pass filtered subbands of an unknown wavelet-transformed high-resolution (HR) image, and then the unknown high-resolution image is produced by estimating the wavelet coefficients of the high-pass filtered subbands. The same approach is used to obtain an initial estimate of the high-resolution image by zero filling the high-pass filtered subbands. Detail coefficients are estimated via feeding this initial estimate to an undecimated wavelet transform (UWT). Taking an inverse transform after replacing the approximation coefficients of the UWT with initially estimated HR image, results in the final interpolated image.
Experimental results of the proposed algorithms proved their superiority over the state-of-the-art enhancement and interpolation techniques
What is the relationship between lightness and perceived illumination
Surface reflectance and illumination level, which are confounded in the
retinal image, must be disentangled by the visual system and a theory of
lightness must explain how. Thus, a theory of surface lightness should also be
a theory of perceived illumination and describe the relationship between
them. Perceived illumination and perceived grey values have been measured
using a new technique. Looking into a vision tunnel, observers saw two square
apertures in the far wall, each revealing a patch of wall composed of two
shades of grey. They adjusted the illumination level in one aperture to match
that in the other. The stimuli placed in the apertures varied in luminance
range, spatial frequency, and relative area. Results show that 1) illumination is
matched for highest luminance (with no effect of spatial frequency).
Combined with earlier findings that lightness is anchored by highest
luminance, this supports Koffka’s suggestion that lightness and perceived
illumination are coupled in an invariant way. 2) Changes in the relative area of
the light and dark shades produced complementary influences on perceived
illumination and surface lightness. That is, when stimulus conditions evoke a
conflict between anchoring the highest luminance at white and anchoring the
largest area at white, enlarging the darker shade causes its lightness to
increase and the perceived illumination to decrease by the same amount,
3
further supporting Koffka. 3) These findings allow perceived illumination
level to now be systematically incorporated into anchoring theory, which until
this point has been solely a theory of surface lightness
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