High resolution image sensors are now standard in imaging devices such as mobile phones with camera functionality. Resolution improvement in very small sensors is obtained by decreasing the pixel size but, in CMOS sen...
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ISBN:
(纸本)9781424424221
High resolution image sensors are now standard in imaging devices such as mobile phones with camera functionality. Resolution improvement in very small sensors is obtained by decreasing the pixel size but, in CMOS sensors, the likelihood of defective pixels also augments. Hence, sophisticated processing is necessary for achieving high quality images despite of noise and defects. This paper presents a hardware/software solution for high precision correction of defective pixels in an image sensor. The method maintains an always up-to-date map of the defective pixels and also allows detection of new defects as they show up during the lifetime of the sensor. The reliability of the map is assured by tracking the history of pixels defectiveness. The map is updated automatically and in real time without user intervention.
Image denoising is one of the most recurrent problems to face in the design of image generation pipelines. This paper proposes a novel method for the estimation of the noise level in images contaminated by additive wh...
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Image denoising is one of the most recurrent problems to face in the design of image generation pipelines. This paper proposes a novel method for the estimation of the noise level in images contaminated by additive white Gaussian noise (AWGN). The estimated noise level is updated on a frame basis allowing convergence to the optimal value. At the same time, dynamic adjustment to changing noise levels is permitted. The proposed technique has been successfully implemented in a real system, demonstrating the validity of the proposed solution.
Digital images captured in dim light conditions can be very noisy: mixtures of different noise types may damage the image signal, e.g. impulsive and Gaussian noises. A spatio-temporal filter is proposed, which is capa...
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Digital images captured in dim light conditions can be very noisy: mixtures of different noise types may damage the image signal, e.g. impulsive and Gaussian noises. A spatio-temporal filter is proposed, which is capable to eliminate multiple adjacent defective pixels and reduce Gaussian noise in the raw data acquired by the image sensor. The proposed solution is adaptive in that it automatically adjusts its sensitivity, depending on the estimated noise.
This work describes a novel technique for fast noise level estimation that can be used both in spatial and temporal filters to tune the filtering strength. The method has been validated by integrating it in a denoisin...
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This work describes a novel technique for fast noise level estimation that can be used both in spatial and temporal filters to tune the filtering strength. The method has been validated by integrating it in a denoising algorithm for joint Gaussian noise reduction and defect correction in raw digital images.
A projective image registration algorithm, oriented to consumer devices, is proposed. It exploits a "multi-resolution feature based method" for estimating the projective parameters through a 2D Daubechies di...
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A projective image registration algorithm, oriented to consumer devices, is proposed. It exploits a "multi-resolution feature based method" for estimating the projective parameters through a 2D Daubechies discrete wavelet transform (DWT). The algorithm has been fully tested with real image sequences acquired by CMOS sensors and compared to other registration techniques. The obtained results highlight the accuracy of the registration parameters.
In dim light conditions, digital images are prone to high noise levels, especially if a low cost imager is used. Gaussian and impulsive noises are the most likely to appear. Furthermore, defective, stuck pixels are qu...
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ISBN:
(纸本)951227065X
In dim light conditions, digital images are prone to high noise levels, especially if a low cost imager is used. Gaussian and impulsive noises are the most likely to appear. Furthermore, defective, stuck pixels are quite unpleasant as well. In low illumination conditions, impulsive noise is particularly annoying;because of the high signal amplification, more than one defective pixel is likely to show tip in the filter mask at the same time. A spatial filter is proposed, capable of removing Gaussian noise. impulsive noise and stuck pixels by using the same processing kernel.
This paper describes a temporal filter aimed at the simultaneous cancellation of fixed pattern noise and temporal noise from image sequences by exploiting all the data provided by a typical image sensor (e.g. CCD/CMOS).
This paper describes a temporal filter aimed at the simultaneous cancellation of fixed pattern noise and temporal noise from image sequences by exploiting all the data provided by a typical image sensor (e.g. CCD/CMOS).
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