Adaptive Correction Technique Research Articles

Underwater image restoration based on light attenuation prior and color-contrast adaptive correction

Underwater imaging is uniquely beset by issues such as color distortion and diminished contrast due to the intricate behavior of light as it traverses water, being attenuated by processes of absorption and scattering. Distinct from traditional underwater image restoration techniques, our methodology uniquely accommodates attenuation coefficients pertinent to diverse water conditions. We endeavor to recover the pristine image by approximating decay rates, focusing particularly on the blue-red and blue-green color channels. Recognizing the inherent ambiguities surrounding water type classifications, we meticulously assess attenuation coefficient ratios for an array of predefined aquatic categories. Each classification results in a uniquely restored image, and an automated selection algorithm is employed to determine the most optimal output, rooted in its color distribution. In tandem, we've innovated a color-contrast adaptive correction technique, purposefully crafted to remedy color anomalies in underwater images while simultaneously amplifying contrast and detail fidelity. Extensive trials on benchmark datasets unambiguously highlight our method's preeminence over six other renowned strategies. Impressively, our methodology exhibits exceptional resilience and adaptability, particularly in scenarios dominated by green background imagery.

Synchronous Driving Method for Stitching Pixel Arrays Based on an Adaptive Correction Technique.

With the application of stitching technology in large-pixel-array CMOS image sensors, the problem of non-synchronized output signals from pixel array bilateral driver circuits has become progressively more serious and has led to the DC perforation of bilateral driver circuits, while conventional clock tree synchronization design methodology does not apply to stitching technology. Therefore, this paper analyses reasons for the inconsistency in the output signals of bilateral driving circuits and proposes a synchronous driving method applicable to stitching pixel arrays based on the idea of on-chip output signal delay detection and calibration. This method detects and corrects the non-synchrony of the row driver output signals on both sides according to changes in the operating environment of the chip. This method is characterized by a simple structure and high reliability. Finally, based on the 55 nm stitching process, simulations are carried out in a CMOS image sensor with a chip area of 77 mm × 84 mm to verify that this method is feasible. This large image sensor with a 150 M pixel array has a frame rate of over 10 FPS.

Rain Area Detection in South-Western Kenya by Using Multispectral Satellite Data from Meteosat Second Generation.

This study presents a rain area detection scheme that uses a gradient based adaptive technique for daytime and nighttime rain area detection and correction from reflectance and infrared (IR) brightness temperatures data of the Meteosat Second Generation (MSG) satellite. First, multiple parametric rain detection models developed from MSG’s reflectance and IR data were calibrated and validated with rainfall data from a dense network of rain gauge stations and investigated to determine the best model parameters. The models were based on a conceptual assumption that clouds characterised by the top properties, e.g., high optical thickness and effective radius, have high rain probabilities and intensities. Next, a gradient based adaptive correction technique that relies on rain area-specific parameters was developed to reduce the number and sizes of the detected rain areas. The daytime detection with optical (VIS0.6) and near IR (NIR1.6) reflectance data achieved the best detection skill. For nighttime, detection with thermal IR brightness temperature differences of IR3.9-IR10.8, IR3.9-WV73 and IR108-WV62 showed the best detection skill based on general categorical statistics. Compared to the Global Precipitation Measurement (GPM) Integrated Mult-isatellitE Retrievals for GPM (IMERG) and the gauge station data from the southwest of Kenya, the model showed good agreement in the spatial dynamics of the detected rain area and rain rate.

Optical modelling of a supplementary tunable air-spaced goggle lens for rodent eye imaging.

Aberration variations severely degrade retinal imaging in small animal eyes. Previously, the approach of a goggle lens with a matching corneal index was proposed to overcome the on-axis resolution limit of static imaging systems, which allows the use of the full eye pupil. But this technique didn’t address the problem of the large power variation, and the ensuing aberration on and off-axis, when dealing with small animal eyes. In this study, we present the concept of a tunable goggle lens, designed to compensate individual ocular aberration for different rodent eye powers. Ray tracing evidences that lens-fitted goggles permit, not only to adjust individual eyes power, but also to surpass conventional adaptive correction technique over large viewing angle, provided a minimum use of two spaced liquids. We believe that the overlooked advantage of the 3D lens function is a seminal finding for further technological advancements in widefield retinal imaging.

Adaptive Correction of Sampling Bias in Dynamic Call Graphs

This article introduces a practical low-overhead adaptive technique of correcting sampling bias in profiling dynamic call graphs. Timer-based sampling keeps the overhead low but sampling bias lowers the accuracy when either observable call events or sampling actions are not equally spaced in time. To mitigate sampling bias, our adaptive correction technique weights each sample by monitoring time-varying spacing of call events and sampling actions. We implemented and evaluated our adaptive correction technique in Jikes RVM, a high-performance virtual machine. In our empirical evaluation, our technique significantly improved the sampling accuracy without measurable overhead and resulted in effective feedback directed inlining.

Adaptive correction technique for 3D reconstruction of fluorescence microscopy images

Recent advances in high-resolution imaging have provided valuable novel insights into structural relationships within cells and tissues both in vitro and in vivo. An analysis of this kind is regularly done by optical sectioning using either confocal or deconvolution microscopy. However, the reconstruction of 3D images suffers from light scattering and absorption with increasing depth by finite transparency of the used media. Photobleaching of fluorochromes has been especially troublesome and often the only remedy for loss of signal during optical sectioning is to reduce the number of sections. This causes disparities in the x-y and z dimensions of voxels, which lead to vertical distortion of the original stack of images and necessitates interpolation. Interpolation is necessary to fill up the gaps between consecutive sections in the original image stack to obtain cubic voxels. The present manuscript describes a novel method for adaptive compensation of attenuation of light intensity in stacks of fluorescence microscopy images that is based on a physical model of light attenuation. First, we use a fast interpolation technique to generate a cubic voxel-based volume stack with the aid of a contribution look up table. With the contribution look up table, multiple calculations are avoided, which substantially reduces the computational time without compromising the accuracy of the restoration procedure. Second, each section within the resulting volume is processed to rectify its intensity values that have been altered due to photobleaching and scattering and absorption. The method allows to define the last good section in the stack and the correction is then done automatically.

Adaptive motion compensation in MR imaging without use of navigator echoes.

Retrospective correction of magnetic resonance (MR) image data to eliminate the effects of patient motion is possible with use of adaptive correction techniques. These methods require an accurate record of the motion that occurs during imaging. The authors evaluated whether motion information suitable for adaptive correction could be obtained from phase-encoded image data alone rather than from separate navigator echoes. Once such displacements were estimated from the image data, motion correction proceeded with use of the same algorithm used for the navigator echoes. The results show that image data alone can be used to effectively measure view-to-view displacements in phantoms, but external markers are required for accurate measurement during axial head imaging of patients.