This paper establishes an efficient color space for the contrast enhancement of myocardial perfusion images. The effects of histogram equalization and contrast limited adaptive histogram equalization are investigated and the one which gives good enhancement results is extended to the suitable color space. The color space which gives better results is chosen experimentally. Uniqueness of this work is that contrast limited adaptive histogram equalization technique is applied to the chrominance channels of the cardiac nuclear image, leaving the luminance channel unaffected which results in an enhanced image output in color space.

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This paper presents a blind de-convolution algorithm for enhancing cardiac SPECT images by reducing the blur present in the image. The method is based on maximum likelihood estimate and in particular, the processing is done in a suitable color space. An iterative algorithm, without any prior information, is used to estimate the original image and the point spread function. Blur metric and peak signal to noise ratio are considered for performance evaluation of the algorithm. The effect of number of iterations on the quality of de-blurred image is also studied. Real medical images are used for appraising the algorithm.

The application of radioactive isotopes for imaging human body parts developed into nuclear imaging technology, including single photon emission computed tomography imaging (SPECT). Visual inspection and interpretation of SPECT images is a challenging task as there is random scattering of photons during the image reconstruction process which affects its contrast. Recognizing even gradual changes in color intensity aids in the interpretation of images. The paper proposes a new image processing technique to enhance cardiac nuclear images generated by a single photon emission computed tomography device by improving the contrast features. The method utilizes the concept of adaptive techniques in morphology. As an initial step, color space conversion is performed to convert the image to a color space suitable for its processing and each slice or tile corresponding to the gated cardiac cycle is extracted. In the second step, the size of the neighbourhood area is selected for the operation of the structuring element. Morphological processing is done as a final step. This methodology can be used as a pre-processing module for computer aided diagnostic systems. The proposed method employs a novel image dependent technique for the enhancement of cardiac SPECT images making use of morphology in a suitable color space. Qualitative and quantitative evaluations prove the effective performance of the proposed algorithm in enhancing cardiac SPECT images. Index Terms-Morphological processing, nuclear medicine imaging, positron emission tomography, single photon emission computed tomography. Since 2008 she has been dedicated to the design and development of signal and image processing systems. She developed a low complexity space time adaptive system algorithm for sonar detection and presented it in 2010 IEEE Sensor Array and Multichannel Signal Processing Workshop conducted in Jerusalem. As an IEEE member for the past 6 years, her research interests include signal processing, image processing and use of adaptive techniques in image processing. Jayasree V. K. received the M.

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