Image Contrast Adjustment Research Articles

A High Dynamic Range Image Fusion Method Based on Dual Gain Image

ABSTRACT For a camera with automatic gain control, two images with high and low optical gain can be output at the same exposure time. Due to the small gain value, most of target details are hidden in the dark pixels for the low gain image, and the brightness saturation usually appears in high gain image for the high luminance areas. To obtain the essential information from the dual gain images, a generation method of high dynamic range image based on dual gain image was developed. The method is composed of five parts, including enhancement of image detail, establishment of Laplacian pyramid, selection of fusion operator, reconstruction of fusion pyramid and adjustment of image contrast. Results showed that combination of the gradient operator for N-1 layer and the neighbourhood filter operator for the Nth layer had better fusion effect. Moreover, based on the analysis of image information entropy and clarity, the fusion efficiency was calculated, and the fusion efficiency of Mertens’s method, Jiang’s method, Zhang’s method, Goshtasby’s method and the presented method was 30.5%, 33.5%, 39.5%, 51% and 99%, indicating that the HDR fusion method based on dual gain image is reliable.

A Variety of Choice Methods for Image-Based Artistic Rendering

Neural style transfer (NST) is a technique based on the deep learning of a convolutional neural network (CNN) to create entertaining pictures by cleverly stylizing ordinary pictures with the predetermined visual art style. However, three issues must be carefully investigated during the generation of neural-stylized artwork: the color scheme, the strength of style of the strokes, and the adjustment of image contrast. To solve these problems and select image colorization based on personal preference, in this paper, we propose modified universal-style transfer (UST) method combined with the image fusion and color enhancement methods to design a good post-processing framework to tackle the three above-mentioned issues simultaneously. This work provides more visual effects for stylized images, and also can integrate into the UST method effectively. In addition, the proposed method is suitable for stylized images generated by any NST method, but it also works similarly to the Multi-Style Transfer (MST) method, which mixes two different stylized images. Finally, our proposed method successfully combined the modified UST method and post-processing method to meet personal preference.

Single Image Defogging Method Based on Image Patch Decomposition and Multi-Exposure Image Fusion.

Bad weather conditions (such as fog, haze) seriously affect the visual quality of images. According to the scene depth information, physical model-based methods are used to improve image visibility for further image restoration. However, the unstable acquisition of the scene depth information seriously affects the defogging performance of physical model-based methods. Additionally, most of image enhancement-based methods focus on the global adjustment of image contrast and saturation, and lack the local details for image restoration. So, this paper proposes a single image defogging method based on image patch decomposition and multi-exposure fusion. First, a single foggy image is processed by gamma correction to obtain a set of underexposed images. Then the saturation of the obtained underexposed and original images is enhanced. Next, each image in the multi-exposure image set (including the set of underexposed images and the original image) is decomposed into the base and detail layers by a guided filter. The base layers are first decomposed into image patches, and then the fusion weight maps of the image patches are constructed. For detail layers, the exposure features are first extracted from the luminance components of images, and then the extracted exposure features are evaluated by constructing gaussian functions. Finally, both base and detail layers are combined to obtain the defogged image. The proposed method is compared with the state-of-the-art methods. The comparative experimental results confirm the effectiveness of the proposed method and its superiority over the state-of-the-art methods.

Single-shot late Gd enhancement imaging of myocardial infarction with retrospectively adjustable contrast and heart-phase

ObjectTo enable a retrospective adjustment of image contrast and heart phase in inversion recovery prepared late gadolinium enhancement (LE) imaging in the myocardium. Materials and methodsAfter one inversion pulse, unsegmented data were acquired over multiple cardiac cycles using a radial spoiled gradient-echo sequence with golden angle increments between subsequent readouts. Model-based acceleration of parameter mapping (MAP) was combined with an image registration technique (“MOCO-MAP”) to enable the reconstruction of images with arbitrary inversion time TI. ResultsMOCO-MAP allowed the reconstruction of LE images with arbitrary TI for arbitrary cardiac phases in four patients suffering from myocardial infarction. Regions with LE agreed well between the MOCO-MAP and the segmented techniques typically applied in clinical routine. ConclusionsMOCO-MAP delivers LE images with arbitrary and thus retrospectively optimized contrast between vital and diseased tissue, without the need for time-consuming TI scouting.

A Novel Method to Control Dominating Gray Levels during Image Contrast Adjustment using Modified Histogram Equalization

Contrast and Brightness are two major factors, which affect the superiority of an image for easy or stainless or pleasant viewing. Overall lighting condition and darkness condition of the image collectively called as brightness, whereas differences in brightness or intensity range between the low and high-intensity value of an image are called as contrast. Histogram equalization is a very famous approach for image contrast adjustment or enhancement in image processing, but which produces sometimes washed out appearance, especially for a small region of the grayscale image. Contrast adjustment is part of the noise filtering or smoothing process, which is essential in automatic identification or recognition systems like a fingerprint or any other biometric-based recognition systems to get higher efficiency. Histogram-based equalization is simple in terms understandability and implementation, which is referred as one of the greatest advantages of this contrast adjustment method. Histogram equalization is less expensive compared to another similar type of contrast adjustment or enhancement algorithm. The novel approach planned in this paper controls dominating gray levels before applying histogram equalization process so that it performs enhancement of the image without over brightness or over darkness, which makes smaller part of the image invisible or loss of details in that portion of the image. This method outperforms histogram equalization method by enhancing the contrast with intermediate brightness or neither too bright nor too dark. In this paper, we compare different types of the grayscale image using the novel method and global histogram equalization method using MATLAB.

A Novel Method to Control Dominating Gray Levels during Image Contrast Adjustment using Modified Histogram Equalization

Contrast and Brightness are two major factors, which affect the superiority of an image for easy or stainless or pleasant viewing. Overall lighting condition and darkness condition of the image collectively called as brightness, whereas differences in brightness or intensity range between the low and high-intensity value of an image are called as contrast. Histogram equalization is a very famous approach for image contrast adjustment or enhancement in image processing, but which produces sometimes washed out appearance, especially for a small region of the grayscale image. Contrast adjustment is part of the noise filtering or smoothing process, which is essential in automatic identification or recognition systems like a fingerprint or any other biometric-based recognition systems to get higher efficiency. Histogram-based equalization is simple in terms understandability and implementation, which is referred as one of the greatest advantages of this contrast adjustment method. Histogram equalization is less expensive compared to another similar type of contrast adjustment or enhancement algorithm. The novel approach planned in this paper controls dominating gray levels before applying histogram equalization process so that it performs enhancement of the image without over brightness or over darkness, which makes smaller part of the image invisible or loss of details in that portion of the image. This method outperforms histogram equalization method by enhancing the contrast with intermediate brightness or neither too bright nor too dark. In this paper, we compare different types of the grayscale image using the novel method and global histogram equalization method using MATLAB.

Automatic x-ray image contrast enhancement based on parameter auto-optimization.

PurposeInsufficient image contrast associated with radiation therapy daily setup x‐ray images could negatively affect accurate patient treatment setup. We developed a method to perform automatic and user‐independent contrast enhancement on 2D kilo voltage (kV) and megavoltage (MV) x‐ray images. The goal was to provide tissue contrast optimized for each treatment site in order to support accurate patient daily treatment setup and the subsequent offline review.MethodsThe proposed method processes the 2D x‐ray images with an optimized image processing filter chain, which consists of a noise reduction filter and a high‐pass filter followed by a contrast limited adaptive histogram equalization (CLAHE) filter. The most important innovation is to optimize the image processing parameters automatically to determine the required image contrast settings per disease site and imaging modality. Three major parameters controlling the image processing chain, i.e., the Gaussian smoothing weighting factor for the high‐pass filter, the block size, and the clip limiting parameter for the CLAHE filter, were determined automatically using an interior‐point constrained optimization algorithm.ResultsFifty‐two kV and MV x‐ray images were included in this study. The results were manually evaluated and ranked with scores from 1 (worst, unacceptable) to 5 (significantly better than adequate and visually praise worthy) by physicians and physicists. The average scores for the images processed by the proposed method, the CLAHE, and the best window‐level adjustment were 3.92, 2.83, and 2.27, respectively. The percentage of the processed images received a score of 5 were 48, 29, and 18%, respectively.ConclusionThe proposed method is able to outperform the standard image contrast adjustment procedures that are currently used in the commercial clinical systems. When the proposed method is implemented in the clinical systems as an automatic image processing filter, it could be useful for allowing quicker and potentially more accurate treatment setup and facilitating the subsequent offline review and verification.

Flexible Fiber-Optic High-Speed Imaging of Vocal Fold Vibration: A Preliminary Report

High-speed video (HSV) imaging of vocal fold vibration has been possible only through the rigid endoscope. This study reports that a fiberscope-based high-speed imaging system may allow HSV imaging of naturalistic voicing. Twenty-two subjects were recorded using a commercially available black and white high-speed camera (Photron Motion Tools, 256 × 120 pixel, 2000 frames per second, 8 second acquisition time). The camera gain is set to +6 db. The camera is coupled to a standard fiber-optic laryngoscope (Olympus ENF P-4) with a 300-W Xenon light. Image acquisition was done by asking the subject to perform repeated phonation at modal phonation. Video images were processed using commercial video editing and video noise reduction software (After effects, Magix, and Neat Video 4.1). After video processing, the video images were analyzed using digital kymography (DKG). The HSV black and white video acquired by the camera is gray and lacks contrast. By adjustment of image contrast, brightness, and gamma and using noise reduction software, the flexible laryngoscopy image can be converted to video image files suitable for DKG and waveform analysis. The increased noise still makes edge tracking for objective analysis difficult, but subjective analysis of DKG plot is possible. This is the first report of HSV acquisition in an unsedated patient using a fiberscope. Image enhancement and noise reduction can enhance the HSV to allow extraction of the digital kymogram. Further image enhancement may allow for objective analysis of the vibratory waveform.

Swarm Intelligence for Automatic Video Image Contrast Adjustment

Video surveillance has become an integrated part of today's life. We are surrounded by video cameras in all the public places and organizations in our day to day life. Many useful information like face detection, traffic analysis, object classification, crime analysis can be assessed from the recorded videos. Image enhancement plays a vital role to extract any useful information from the images. Enhancing the video frames is a major part as it serves the further analysis of video sequences. The proposed paper discusses the automatic contrast adjustment in the video frames. A new hybrid algorithm was developed using the spatial domain method and Artificial Bee Colony Algorithm (ABC), a swarm intelligence based technique for image enhancement. The proposed algorithm was tested using the traffic surveillance images. The proposed method produced good results and better quality picture for varied levels of poor quality video frames.

A spiral based image watermarking scheme using Karhunen–Loeve and discrete hartley transforms

The main objective of developing the image watermarking technique is satisfying the robustness and the imperceptibility of multimedia protection. To achieve this objective, a novel hybrid image watermarking scheme based on Karhunen Loeve transform (KLT) and discrete hartley transform (DHT) and is proposed. In the proposed scheme (KL---DHT based watermarking scheme), the original image is divided into blocks using spiral scan, then the DHT is calculated for each block, after that, the KLT is applied for each DHT block. The watermark embedding process is carried out during the KLT transformation process. In the watermark extracting process, the watermarked image is distorted using several image attacks such as JPEG image compression, image rotation, image resizing, adding noise (Gaussian, impulsive or speckle) or image contrast adjustment using adaptive histogram equalization. Furthermore, the proposed scheme is carried out using block by block image scan and the achieved results are compared with those obtained from other watermarking schemes such as discrete cosine transform/singular value decomposition (DCT---SVD) based watermarking scheme, discrete wavelet transform/SVD (DWT---SVD) based watermarking scheme and SVD watermarking in the homomorphic domain watermarking scheme. The achieved results proved that, the superiority of the KL---DHT based watermarking scheme with spiral scan compared to other watermarking schemes in the presence of different image attacks.

Medical Image Contrast Enhancement Using Spline Concept: Data from the Osteoarthritis Initiative

Excellent visual quality of medical image is important for subsequent image interpretation and diagnosis planning. Hence, preservation of brightness and considerable tissue contrast improvement are essential for this purpose. Previous histogram equalization methods tend to focus on brightness preservation and neglect the need to address excessive contrast enhancement. However, gray level medical images are highly sensitive to redundant adjustment of image contrast. In this work, we propose to implement cubic spline to reduce the difference in pixel intensity prior to histogram equalization while retaining the partition of histogram to prevent dramatic mean brightness shift in resultant image. Qualitative results indicate that our proposed contrast enhancement method is capable of avoiding extreme brightness elevation and excessive tissue contrast improvement to provide holistic views of the knee MR images. In future, we would like to recommend the development of adaptive data interval to substitute the uniform data point intervals.

Analytical Adjustment of Image Contrast

Detailed analysis based on histogram stretching for image contrast adjustment has been performed. However unprocessed image includes unwanted noise which needs to be reduced for performing the stretching accurately. The level of noise reduction greatly effects the contrast adjustment and varies from images to images depending on the intensity of noise itself. This paper discusses about image contrast adjustment technique along with the algorithm. Results are analyzed corresponding to images of different quality based on histogram stretching considering different level for the noise reduction. General Terms Histogram stretching, Visual quality, Image contrast

Geometrical triple phase boundary length measurement using focused ion beam tomography

AbstractIn multi‐component materials, triple phase boundary (TPB) is the location where reactions occur. A typical example is the TPB encountered in solid oxide fuel cells at the cathode–electrolyte interface. We proposed a tomographic approach that was developed based on serial sectioning using a focused dual ion beam (FIB) system. For image capture, FIB tomography was coupled with scanning electron microscopy, and differentiation of the composite cathode materials was possible through image contrast adjustment. An algorithm, built on the Hoshen–Kopelman theory, was then applied to measure TPB length. The percentage of the connected TPB line was also calculated with the algorithm for 3D computation. © 2011 Canadian Society for Chemical Engineering

Inter-observer comparison of target delineation for MRI-assisted cervical cancer brachytherapy: Application of the GYN GEC-ESTRO recommendations

Background and purpose To investigate the inter-observer variation of target contouring when using the GYN GEC-ESTRO recommendations for MR image-guided brachytherapy (IGBT) for cervical cancer. Materials and methods Nineteen cervical cancer patients, treated by radiotherapy at the Institut Gustave Roussy (IGR) in France ( n = 9) or at the Medical University of Vienna (AKH) in Austria ( n = 10) were included in this study. IGBT was used for all patients. Two radiation oncologists, one from IGR and the other from AKH, outlined the target volumes on MRI at the time of brachytherapy according to the GYN GEC-ESTRO recommendations. The absolute, common and encompassing volumes and their conformity indices (CIs) were assessed for the GTV, HR CTV and IR CTV. D90 and D100 for each volume were assessed. Visual evaluation was made to assess the reasons for the most frequent inter-observer differences. Results The mean volumes of GTV and HR CTV did not differ significantly between the observers, p > 0.05. Significant differences were observed only for the mean volumes of the IR CTV of both centres, p < 0.05. CIs ranged from 0.5 to 0.7. DVH-parameter analyses did not reveal any statistical differences, except for the D100 for the GTV at AKH, and the D90 for the IR CTV at IGR, p < 0.05. Underlying reasons for inter-observer differences included image contrast adjustment and neglecting to consider anatomical borders. Conclusions The results of this inter-observer study show that the application of the GYN GEC-ESTRO recommendations for IGBT contouring at two different institutions with two different traditions for applicators, CTV assessment, MR image acquisition and dose prescription is feasible, and it produces acceptable inter-observer variability.