Search

The presence of haze degrades the quality of a captured image. The aerosols in the atmosphere cause scattering of the incident light, and this phenomenon is observed on the captured image as well, where some regions appear grayish and colors in those regions appear faded. To improve the quality of the hazy images, we propose a joint fusion and restoration model that sufficiently enhances the contrast of the hazy image while preserving its mean brightness. The fusion model utilizes images of various exposures generated by a modified Gamma correction model. The images for fusion are selected using some selection criteria and fused in a multi-resolution decomposition scheme. Three haze-sensitive weight maps corresponding to some statistical property of haze namely, saliency, illumination, and luminance gradient are constructed. The hazy image formation model is then used and dehazing is performed based on the dark channel prior assumption. The proposed algorithm does not consider the estimation of airlight vector which seldom cause over-saturation defect, instead a mean brightness preservation model has been applied. The variety of experiments demonstrate the significance of the proposed method.

A phase error compensation method is proposed for phase measurement profilometry. The gamma nonlinearity of a projector–camera pair can induce higher-order harmonics in a deformed pattern, resulting in periodic phase errors in the unwrapped phase map. To reduce the phase error caused by gamma nonlinearity, a model relating the phase error and practical wrapped phase is established, and a phase matrix for compensation is obtained based on the model instead of solving the gamma value of the projector–camera pair (γ). In addition, the compensation accuracy theoretically decreases with the ratio of the third-harmonic coefficient to the fundamental frequency components of the deformed pattern (β). The simulated measurement shows that the root-mean-square (RMS) before and after compensation is 0.0052 and 2.6840 × 10 − 4 rad when β is 0.0063, respectively, and it is 0.0755 and 0.0175 rad when β is 0.0880, respectively. The experimental results indicate that the RMS of the unwrapped phase in a uniform plane before and after compensation is 0.0639 and 0.0156 rad, respectively, when β is ∼0.09 using the proposed method. The periodic phase error caused by gamma nonlinearity decreases dramatically using the proposed method.

As an extra option, fine grayscale data that exceed eight bits per pixel are encoded into pseudogray colors in 8-bit sRGB color space to be displayed on an 8-bit sRGB CRT monitor. The characteristics of the pseudogray are investigated in terms of the CIELAB color difference and a*b* coordinates. © 2003 Society of Photo-Optical Instrumentation Engineers.

We propose a method to compensate for the projector intensity nonlinearity induced by gamma effect in three-dimensional (3-D) fringe projection metrology by extending high-order spectra analysis and bispectral norm minimization to digital sinusoidal fringe pattern analysis. The bispectrum estimate allows extraction of vital signal information features such as spectral component correlation relationships in fringe pattern images. Our approach exploits the fact that gamma introduces high-order harmonic correlations in the affected fringe pattern image. Estimation and compensation of projector nonlinearity is realized by detecting and minimizing the normed bispectral coherence of these correlations. The proposed technique does not require calibration information and technical knowledge or specification of fringe projection unit. This is promising for developing a modular and calibration-invariant model for intensity nonlinear gamma compensation in digital fringe pattern projection profilometry. Experimental and numerical simulation results demonstrate this method to be efficient and effective in improving the phase measuring accuracies with phase-shifting fringe pattern projection profilometry.

Fringe projection profilometry (FPP) using a digital video projector is widely used for three-dimensional shape measurement. However, the gamma nonlinearity, system vibration, and noise cause the captured fringe patterns to be nonsinusoidal waveforms and have a grayscale deflection from their true value. This leads to an additional phase measurement error for a general phase-shifting algorithm. Based on the theoretical analysis, we propose a method to eliminate the phase error considering two factors. In this method, four-step phase-shifting is done four times with an initial phase offset of 22.5 deg and the average of these four phase maps precisely results in the real phase. As a result, phase error caused by gamma nonlinearity can be effectively suppressed. In addition, every image in phase shifting is replaced by the average of 20 fringe images continuously captured at the same state to avoid the phase error caused by system vibration and noise. Experimental results show that this method is effective in eliminating the phase error in practical phase-shifting FPP. In general, more than 90% of the phase error can be reduced.

Spot estimation accuracy of Shack-Hartmann images and its impact on Airborne Aero-Optic Laboratory (AAOL) wavefront statistics are addressed. A study is conducted of an individual spot simulated using a double sinc function under varying degrees of additive non-zero mean Gaussian noise within a 15×15 pixel area-of-interest. The focus of this paper is two-fold. First, the accuracy of four existing centroiding methods including first moment, convolution, Gaussian, and weighted first moment are compared. It is found that the weighted first moment centroid most accurately estimates spot centers but requires significantly more computational time with respect to the first moment method. Second, three image-processing techniques, including gamma correction, thresholding, and windowing, are analyzed to determine their influence on each centroiding method’s spot estimation accuracy. A fourth order gamma correction significantly reduces spot estimation error for three centroiding methods. The key result is that the accuracy of the first moment centroid with an applied gamma correction is comparable to the weighted first moment without the computational burden. Finally, the first moment centroid with gamma correction and weighted first moment centroid are applied to AAOL flight data. Wavefront statistics are computed and compared to the commonly used first moment centroid.

Existing phase-shifting measurement methods involve processing of three acquired images or computation of functions that require more complex processing than linear functions. This paper presents a novel two-step triangular-pattern phase-shifting method of 3-D object-shape measurement that combines advantages of earlier techniques. The method requires only two image-acquisition steps to capture two images, and involves projecting linear grayscale-intensity triangular patterns that require simpler computation of the intensity ratio than methods that use sinusoidal patterns. A triangular intensity-ratio distribution is computed from two captured phase-shifted triangular-pattern images. An intensity ratio-to-height conversion algorithm, based on traditional phase-to-height conversion in the sinusoidal-pattern phase-shifting method, is used to reconstruct the object 3-D surface geometry. A smaller pitch of the triangular pattern resulted in higher measurement accuracy; however, an optimal pitch was found, below which intensity-ratio unwrapping failure may occur. Measurement error varied cyclically with depth and may partly be due to projector gamma nonlinearity and image defocus. The use of only two linear triangular patterns in the proposed method has the advantage of less processing than current methods that process three images, or methods that process more complex functions than the intensity ratio. This would be useful for high speed or real-time 3-D object-shape measurement.