Radiographic image enhancement. Part I: spatial domain techniques.

IMECO: A Reconfigurable FPGA-based Image Enhancement Co-Processor Framework

Nowadays, digital images can be easily obtained, recorded and processed in accordance with the widespread use of digital cameras and personal computers. There is an image enhancement as one of most general image processing techniques. In the image enhancement, unsharp masking (UM) has been used widely because its algorithm is very simple and can produce good results. However, over-enhancement occurs in edge parts of the image. Additionally UM also is easy to generate artifacts such as jaggy and halo. To cope with these problems, the authors proposed the selective UM method based on the edge-preserved smoothing filter. However, the image quality obtained by our method depends on values of the enhancement parameters, and their optimal values vary according to user's liking. In this paper, we propose an image enhancement system considering the user's liking by using an interactive genetic algorithm (IGA). In the proposed system, the IGA optimizes the parameters of the image enhancement. Further, a new genetic operation is introduced in order to achieve the effective search in the IGA of the proposed system. Through the experiments using some images, the effectiveness of the proposed system is verified.

Background: Fiducial markers are objects placed in the field of view of an imaging system for use as a point of reference or a measure. There is no information regarding suitable markers for joint models. Objectives: We compared the fiducial markers commonly used in X-ray, CT, and MRI imaging modalities. Methods: The markers tested were plastic balls, ceramic balls, passive reflective balls, liquid-filled balls, and steel balls. The balls were scanned using X-ray, CT, and MRI systems. The scanned X-ray images were reviewed if it the markers are able to be expressed. The tomographic images of CT and MRI were converted into 3D ball models and then the reconstructed shapes and dimensions of the balls were examined. The dimensional accuracy of expression and reconstruction was calculated in terms of the mean and the standard deviation. Results: There was no marker that can be expressed in all the imaging modalities. Alternatively, we propose a synthetic marker that is composed of a hard sphere and a fat tissue wrapping. The hard ball is for X-ray and CT imaging, while the fat tissue is for MRI imaging. Conclusion: A synthetic marker composed of a hard sphere and a fat tissue wrapping can a multimodal fiducial marker. Keywords: Accuracy, fiducial marker, multimodal, registration

Dental, oral and maxillofacial region are very sensitive so low radiation imaging technique like Cone Beam Computed Tomography (CBCT) is useful for investigation of diseases. But due to low radiation, quality of images is not fine they have noise and low contrast in visual impression. So for dentistry diagnostic purpose it is important to pre-process the CBCT image. This paper focuses on improvement of contrast, brightness and noise reduction of dental CBCT images by using Bi Histogram Equalization technique with bent activation function and adaptive median filter for noise reduction. The output image has been analyzed and evaluated using peak value ratio in term of Signal versus Noise (PSNR) and matrix of Structure in term of Similarity Index (SSIM). From the experimental results, it has been found that the adaptive median and Bi histogram with bent activation function has a better noise and enhancement capability as compare to convectional histogram method.

SUMMARYTo restrain pseudo‐Gibbs phenomenon, low contrast and blurred phenomenon in the process of image enhancement, a new method based on the nonsubsampled contourlet transform and the unsharp masking is proposed in this paper. The proposed method utilizes the shift‐invariance of nonsubsampled contourlet transform to restrain the pseudo‐Gibbs phenomenon, and then enhance details of the image by unsharp masking. We achieved an increase in image definition by 54.5%, the mean increased by 15.6%, whereas the standard deviation increased by 54.5% compared with the unsharp masking method. To the noisy image, we achieved an increase in image definition by 35.4%, the mean increased by 2.2%, whereas the standard deviation increased by 34.9% compared with the unsharp masking method. Copyright © 2013 John Wiley & Sons, Ltd.

The present clinical trial was intended to clarify whether subjective assessments of diagnostic X-ray image quality achieved via hand-held (HH) Nomad Pro 2 (KaVo Kerr, Brea, CA, USA) X-ray device is non-inferior that of the wall-mounted (WM) KaVo Focus (KaVo Dental, Bieberich, Germany). A prospective, cross-over, and in vivo non-inferiority clinical trial was conducted to compare these two diagnostic modalities. Based on sampling calculations, 205 patients were selected for study, generating 410 paired bitewing radiographs in randomized sequence. The films were assessed independently, engaging three observers blinded to modality for random, side-by-side-comparisons. Diagnostic image quality was rated as follows: no preference, HH preference, or WM preference. Observer judgements were combined accordingly to reach a majority. Collective observer ratings indicated no preference for diagnostic image quality in 63.9% of cases, with WM preference at 16.6% and HH preference at 19.5%. The difference in HH and WM preferences (19.5%-16.6% = 2.9%) was within the expected 95% confidence interval. Majority agreement was reached in 82.7%. Subjectively assessed diagnostic image quality in bitewing radiographs acquired by HH and WM devices did not differ significantly. The hand-held device is thus non-inferior to the WM in this regard. Our data set of paired bitewing radiographs may subsequently aid in future research.

Autonomous multisensor tracking surveillance system

Accurate detection of egg fertility is crucial to improve hatching success in duck farming. Conventional candling methods rely heavily on human expertise, making them subjective and error-prone. This study proposes an automated classification system for Cihateup duck egg fertility using candling images and a convolutional neural network (CNN) based on the EfficientNet-B3 architecture. Image enhancement techniques, including contrast limited adaptive histogram equalization (CLAHE), unsharp masking, and adaptive thresholding, were applied to improve image quality and feature visibility. The dataset consisted of fertile and infertile egg images captured at two incubation stages: the first 24 hours and the 8th–15th days. Data were split into training, validation, and testing sets with a ratio of 70:15:15. Experimental results show that image enhancement significantly improves classification performance. Without enhancement, the model achieved an accuracy of 49% with an area under curve (AUC) of 0.4226, indicating poor discrimination capability. With image enhancement, the proposed method achieved accuracies of 77% for the first 24 hours dataset and 80% for the 8th–15th days dataset, with AUC values of 0.9962 and 0.9317, respectively. These results demonstrate that EfficientNet-B3 combined with image enhancement provides an effective and computationally efficient solution for automated fertility detection of Cihateup duck eggs.

With fast growth in Internet and digital imaging knowledge, there are progressive customs to simply generate, distribute and allocate the images. Measured the association among digital imaging and privacy fortification, Visual Cryptography and Secret Image Sharing is an inclusive preamble to original security methods. The secret sharing control system is used to guard unauthorized data access and to secure distribution of responsive information. An efficient color image visual cryptic filtering scheme is to improve the image quality on restored original image from visual cryptic shares. The color image visual cryptic filtering scheme presents a deblurring effect on the non-uniform distribution of visual cryptic share pixels. Fourier transformation and texture overlapping is applied to normalize the unevenly transformed share pixels on the original restored image. This in turn improves the quality of restored visual cryptographic image to its optimality. The privacy preservation in visual cryptography plays a major role to provide an efficient secure communication for the users. To address data sharing issues more sensitively, a privacy preservation achieved by using cache-cache mechanism. The cache-cache mechanism maintains a cache inside a cache to preserve the details about the users who shared the secret parts of digital document, which has been splitted in a scheme of visual cryptography. In this work, the binary spanning trees are used to enhance the progress of secure distributed file sharing in visual cryptography. Privacy of file sharing is done with file block id relating to the participant id using binary trees. Group dynamics is handled effectively with distributed key exchange model, based on the principal operation of minimum spanning tree variants. Experimentation carried out with bench mark data sets of real and synthetically generated data sets to estimate the performance of the proposed controlled adaptable distributed file sharing with multiple participants in visual cryptography in terms of group dynamic rate, tree spanning length and privacy overhead.

The images obtained by X-Ray or computed tomography (CT) may be contaminated with different kinds of noise or show lack of sharpness, too low or high intensity and poor contrast. Such image deficiencies can be induced by adverse physical conditions and by the transmission properties of imaging devices. A number of enhancement techniques in image processing may improve the quality of the image. These include: point arithmetic operations, smoothing and sharpening filters and histogram modifications. The choice of the technique, however, depends on the type of image deficiency. In this paper, the primary aim is to propose an efficient image enhancement method based on nonparametric estimation so as to enable medical images to have better contrast. To evaluate the method performance, X-Ray and CT images have been studied. Experimental results verify that applying this approach can engender good image enhancement performance when compared with classical techniques.

Characteristics of the lesions in digital mammography images will be more clear after image enhancement, which can increase the detection rate of early breast cancer. This paper proposes a modified unsharp masking approach based on an improved high-pass filter. Experimental result of digital mammography image enhancement proves that the proposed method can effectively extrude the edges of lesions and at the same time can suppress the noises in uniform background areas.

Digital image processing forms core research area with in computer science disciplines. Rapid growth of image processing technologies has been used digital images more and more prominent in our daily life. Brightness preservation is a technique of improving the image brightness so that the limitations contained in these images is used for various applications in a better way. The contrast enhancement techniques capable to clean up the unwanted noises and enhance the image’s brightness and contrast. In this project aimed to recover the original form of the image and video taken without presence of proper lighting effect. The previous techniques used are histogram equalization, gamma correction for contrast and brightness enhancement in image, here the improved version to overcome the noise and contrast enhancement by the FFT, Bi-log transformation and NTSC are used for both image and video quality improvement.

Magnetic resonance image plays an important role in modern disease diagnosis. In view of the local area contrast of such image is low and the usual magnetic resonance image enhancement method often appears noise enlarging, an magnetic resonance image contrast enhancement algorithm based on contour let transform is proposed. Firstly, the magnetic resonance image is decomposed by contour let transform and get a series of sub band images, then the low-pass sub band is enhanced with piecewise linear transformation, the band pass sub-bands coefficients are revised by a new nonlinear enhancement operator, finally, it obtained the enhancement image after inverse contour let transform. The simulation results show that the contrast enhancement method can not only enhance magnetic resonance image tiny details but also avoid the noise enlarging, the image has better visual effect, which is beneficial to analyze and diagnose disease for doctors.

Acute or chronic sinusitis is a common illness among adults and children. Sinus radiography is the primary imaging study that most otolar-yngologists utilize when diagnosing sinusitis. In this study, we recruited 42 patients (26 males and 16 females) with age ranging from 5 to 83 years (average: 52.3 years) without a history of trauma or neoplasm, between January 2008 and July 2009. Upon receiving a diagnosis of sinusitis, the patients received sinus radiography followed by computed tomography (CT) within two weeks. Images of both sinus radiography and CT were reviewed retrospectively and compared with each other. The results showed that CT confirmed sinus fluid accumulation in all 42 patients, 39 of them were identified with sinus fluid accumulation or opacification by sinus radiography alone, the sensitivity of 92.9%. For individual paranasal sinus, the sensitivities of sinus radiography for discerning fluid accumulation or opacification in maxillary, frontal, ethmoid, and sphenoid sinuses were 88.6%, 88.9%, 57%, and 28.6%, respectively. Our study confirmed that sinus radiography had a higher sensitivity in detecting fluid accumulation or opacification in the maxillary and frontal sinuses, sinus radiography remains a useful imaging modality in assessing sinusitis in clinical settings.

Vignetting refers to a position dependent loss of light in the output of an optical system causing gradual fading out of an image near the periphery. In this paper, we propose a method for correcting vignetting distortion by introducing nonlinear model fitting of a proposed vignetting distortion function. The proposed method aims for embedded digital imaging applications as well as conventional image enhancement. We could obtain a light intensity profile distribution without precisely controlled illumination and considerably reduce memory requirement for vignetting correction compared with the traditional lookup table (LUT) methods. We show the effectiveness of the proposed method by presenting the experimental results obtained from commercial digital cameras.