Lingxue Wang

Real-time color transfer system for low-light level visible and infrared images in YUV color space

A real-time color transfer system based on 3 pieces of multi-media DSP TM1300 for low-light level visible(LLLV) and infrared(IR) images is built. Computing quantity is split among three TM13003. Two pieces of TM1300 preprocess the dual-band images and calculate their mean and standard deviation respectively. The third TM1300 executes fusion and color transfer in YUV space: Firstly the two preprocessed images are fused into one primary color image(source image) in which hot targets present warm color, cold targets present cool color. Then the mean and standard deviation of source images in Y, U, V components are deduced by preprocessed images pixel value and their mean and standard deviation. Finally, the Y, U and V component of source image are scale by the variation ratio of a day-time color image(target image) to the source image. The color and luminance distribution of the target image is transferred into source image and makes it present a sort of day-time color appearance. Comparing to the usually used l&agr;&bgr; space, color transfer in YUV space can avoid iterative color space transformation, logarithmic and exponential calculation, and thus be effective in real-time realization while the color transferred results are acceptable.

Color fusion algorithm for visible and infrared images based on color transfer in YUV color space

Color fusion algorithm for visible and infrared(IR) images based on color transfer in YUV color space under trees, lawn, or land background is presented. Considering the red color will alert observers to possible interested target or danger, this paper aims at working on an algorithm that emphasizes hot targets in IR image with intense red, and the background details in visible image present natural color similar to a color day-time image. V component of YUV space represents the difference between red and Y. Properly increasing the V value will obtain intense red color. Therefore, a nonlinear transfer method based on local mean value of the IR image is proposed. A window of size 5x5 is used to locate hot target in IR image. When the local gray mean value in this window is larger than the global mean value, we determine that this pixel is in a hot area. Then its V value is increased by the ratio of the local gray mean value to the global mean value. Tests show that this method pops out the hot targets with intense red color while the background rendered natural color appearance.

Color fusion schemes for low-light CCD and infrared images of different properties

Although gray-level fused images can optimally integrate the modalities of low-light CCD and infrared imager, operators cannot tell from which modality the details originate. Thus the fundamental that human eyes can discern much more color categories than gray levels has been used to assigns a distinct color to each sensor modality. But the color fused image which has no natural appearance will fatigue operators greatly. Our approach is building on MIT scheme and aims at achieving natural appearance in the color fused image. MIT scheme derives its basis from biological models of color vision and utilizes the feed-forward center-surround shunting neural network to enhance and fuse low-light and infrared images. We bring forward linear fusion architecture, and composite architecture that comprises the enhancement part of MIT scheme and the linear fusion architecture. Furthermore, enhancement and combination methods for low-light and infrared images of different properties have been specified.

Color night vision based on color transfer in YUV color space

To obtain a color night vision image, we proposed a color transfer algorithm in YUV color space based on the color transfer algorithm in lαβ color space which Reinhard proposed. After rendering the simple statistics (means and standard deviations) of the target image to the source image, the color appearance of the target image is transferred to the source image. 2D chromatic histogram (UV histogram) which can help to find an appropriate target image is established. Finally, we illustrated several examples of color transfer to multi-band fused images which are fused in MIT fusion scheme. After a color fused image is obtained, the color transfer is executed to render the color information of the target image to the fusion image. The final image could have a day-like color appearance. Besides, the algorithm has less operation than which in lαβ color space because of less transform complexity. It can be realized in real time in digital signal processors without color space transformation between RGB and YUV.

Sub-pixel processing algorithm of the reducing boundary recursive error in staring FPA micro-scanning imaging

By analyzing the error distribution rule of the boundary recursive reconstruction algorithm in controlled micro-scanning, a sub-pixel image processing algorithm is proposed to reduce the error. The gray statistical principle is used in the algorithm to optimize the error and acquire the sub-pixel image that approximates the original image. The simulation result shows that the eect of this algorithm is better than the over-sample and simple boundary recursive algorithm (BRA), and it results in a good effect both in those of visible light and infrared imaging systems. Therefore, the application of this algorithm will enhance the performance of optoelectronic imaging systems.

Color transfer based on steerable pyramid and hot contrast for visible and infrared images

A color transfer scheme for visible and infrared images is presented. Two main procedures are included: image fusion using steerable pyramid in YUV color space, color transfer based on local mean value of infrared image to enhance hot contrast. Firstly, visible and infrared images are decomposed into 18 subband images with a 4-scale 4-oriatation steerable pyramid that contains one highpass subands, one lowpass subband and sixteen bandpass subbands. In each suband image, Y component of the fused image is formed by the pixels whose value is the larger one between the visible and infrared images. The weighted subtracting operations between visible and infrared constitute the U and V components. Then, during the process of color transfer, the local gray mean in the 5×5 window of the infrared image is concerned. The V component that represents the difference between luminance(Y) and red color is increased by the ratio of the local mean value to the global mean value. Therefore, the hot contrast of infrared is enhanced by rendering hot targets intense red color. Test results show that, the image fusion with the 4-scale 4-oriatation steerable pyramid multiples the paths to transfer the color and luminance of a target image into the fused images, thus, the transferred images are much more colorful, and synchronously reserve the two images advantage that the visible image is good at situation awareness and the infrared image is superior in target detection.

Digital Thermal Microscope for Biomedical Application

In order to analyze the biomedical, we proposed a novel digital thermal microscope based on the uncooled focal plane detector, aiming to achieve the long-wave infrared microscope image, especially for biomedical analysis. Both the mathematical mode of noise equivalent temperature difference (NETD) and the noise equivalent eradiation difference (NEED) were established for micro thermal imaging system. Based on the mathematical model, some measures were taken to increase the system temperature resolution. Furthermore the uncooled focal plane arrays has inherent non-uniformities, so we proposed an adaptive algorithm that can complete NUC by only one frame. Results of our thermal microscope have proved that NUC can weaken striping noise greatly and plateau histogram equalization can further enhance the image quality. The software for the thermal microscope is provided based on Visual C++ and the methods mentioned above. Results of real thermal image experiments have shown that the digital thermal microscope is designed successfully and achieves good performance. With the thermal microscope, minute sized thermal analysis can be achieved. Thus it will become an effective means for diagnosis and the detection of cancer, and it can also accelerate the development of methods for biomedical engineering. The system is very meaningful for academic analysis and is promising for practical applications.

A grayscale image color transfer method based on region texture analysis using GLCM

In order to improve the performance of grayscale image colorization based on color transfer, this paper proposes a novel method by which pixels are matched accurately between images through region texture analysis using Gray Level Co-occurrence Matrix (GLCM). This method consists of six steps: reference image selection, color space transformation, grayscale linear transformation and compression, texture analysis using GLCM, pixel matching through texture value comparison, and color value transfer between pixels. We applied this method to kinds of grayscale images, and they gained natural color appearance like the reference images. Experimental results proved that this method is more effective than conventional method in accurately transferring color to grayscale images.

Performance evaluation of CCD imaging systems with the square integral method based on MRC

The Square Integral Method based on the Minimum Resolvable Contrast (MRC) is to be introduced in this paper as an evolution for the design and evaluation of optoelectronic imaging systems. It is well known that there exists an optimal angle magnification which can make optoelectronic imaging systems and human eye matching optimally, so that optoelectronic imaging systems can performance best. Based on MRC (Minimum Resolvable Contrast) and channel width, a new method called Square Integral (SQI) method was presented for evaluating the general performance of a CCD imaging system, and attaining the optimal angle magnification or optimal viewing distance. Results calculated with this method are in good agreement with the experimental measurements. From the agreement between the practical use and the theoretical predictions for the variation of CCD size, optical focus, luminance and human vision, it demonstrates that the SQI method is an excellent universal measure for the optimal angle magnification and the performance of CCD imaging systems.

General performance evaluation on thermal imaging systems with the square integral method based on MRTD channel width

The Square Integral (SQI) Method based on MRTD (Minimum Resolvable Temperature Difference) is introduced for the design and evaluation of thermal imaging systems. It is well known that there exists an optimal angle magnification which can make optoelectronic imaging systems and human eye matching optimally, and make optoelectronic imaging systems attaining the optimal performance. Based on MRTD and channel width, a new way called SQI method is presented for evaluating the universal performance on thermal imaging systems, and attaining the optimal angle magnification or optimal viewing distance. The method can give a rational description for the matching between thermal imaging systems and human eye. Results calculated with this method are in agreement with experiment measurements quite perfectly. From the coherence between measurement data and theoretical predictions with variable detector size, optics focus, luminance and human vision, it appears that the SQI method is an excellent synthesized measure for the optimal angle magnification and the performance of thermal imaging systems.