Image processing for quality improvement

Schreiber, William F.

doi:10.1109/proc.1978.11172

Cited by 57 publications

(20 citation statements)

References 21 publications

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“…11 Homomorphic filtering, for instance, attempts to attenuate the irradiance component. This distorts shading and, thereby, hampers the perception of physical shapes [24], [27]. See Fig.…”

Section: Resultsmentioning

confidence: 99%

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Lightness determination at curved surfaces with applications to dynamic range compression and model-based coding of facial images

Blohm

1997

IEEE Trans. on Image Process.

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Lightness algorithms, which have been proposed as a model for human vision, are aimed at recovering surface reflectance in a close approximation. They attempt to separate reflectance data from illumination data by thresholding a spatial derivative of the image intensity. This, however, works only reliable in a world of plane Mondrians. An extension of the classical lightness approach of Land and McCann (1971) to curved surfaces is presented. Assuming smooth surfaces with Lambertian reflection properties and leaving aside occlusions and cast shadows, the separation of those components of the intensity gradient due to reflectance from those due to irradiance is posed as a constraint minimization problem. To do so, two classification operators were introduced which identify potential reflectance and irradiance data using a scale-space filtering approach. Two exemplary applications of the proposed extended lightness algorithm in the field of visual telecommunications are presented: (i) the simulation of more uniformly illuminated videophone portrait scenes to give dynamic range compressed images with a most realistic appearance and (ii) the synthesis of videophone portrait images from model-based coded data with a correct illumination effect. In both applications, the extended lightness algorithm is employed for estimating the reflectance functions at facial surfaces. Results obtained by applying the extended lightness algorithm are compared with results obtained by conventional methods known from literature.

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“…11 Homomorphic filtering, for instance, attempts to attenuate the irradiance component. This distorts shading and, thereby, hampers the perception of physical shapes [24], [27]. See Fig.…”

Section: Resultsmentioning

confidence: 99%

“…However, these assumptions do usually not apply to human faces. At them, irradiance and reflectance have rather similar spectra, containing both high-and lowfrequency components (see, e.g., [27]). determining relative reflectance functions at curved surfaces.…”

Section: Discussionmentioning

confidence: 99%

Lightness determination at curved surfaces with applications to dynamic range compression and model-based coding of facial images

Blohm

1997

IEEE Trans. on Image Process.

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“…it is a single input/output transfer function. A modified parameterized function was proposed by Schreiber in [W. F. Schreiber, 1978] as: image,…”

Section: The Nonlinear Log Transformmentioning

confidence: 99%

Fusion of Visual and Thermal Images Using Genetic Algorithms

Erkanli¹

2012

Bio-Inspired Computational Algorithms and Their Applications

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“…To compensate for this effect and to have constant watermark visibility over all image intensities, a lightness function is applied to the image before contrast computation. We use the modified log characteristic proposed by Schreiber [18]:…”

Section: A Lightness Functionmentioning

confidence: 99%

A vision-based masking model for spread-spectrum image watermarking

Kutter

Winkler

2002

IEEE Trans. on Image Process.

161

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Abstract-We present a perceptual model for hiding a spreadspectrum watermark of variable amplitude and density in an image. The model takes into account the sensitivity and masking behavior of the human visual system by means of a local isotropic contrast measure and a masking model. We compare the insertion of this watermark in luminance images and in the blue channel of color images. We also evaluate the robustness of such a watermark with respect to its embedding density. Our results show that this approach facilitates the insertion of a more robust watermark while preserving the visual quality of the original. Furthermore, we demonstrate that the maximum watermark density generally does not provide the best detection performance.

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Image processing for quality improvement

Cited by 57 publications

References 21 publications

Lightness determination at curved surfaces with applications to dynamic range compression and model-based coding of facial images

Lightness determination at curved surfaces with applications to dynamic range compression and model-based coding of facial images

Fusion of Visual and Thermal Images Using Genetic Algorithms

A vision-based masking model for spread-spectrum image watermarking

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