Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The authors introduce a lossless data compression technique based on the morphological skeleton representation. Mathematical morphology is a methodology for image analysis which provides a means for describing the geometrical structure of an image quantitatively. A morphological skeleton representation is a useful means of illustrating the geometrical properties of an image (such as shape, size, and orientations). Since it is capable of extracting the minimum underlying geometry of an image, it can also reduce the entropy of an image (data compression). In the present work, the compression ratio is calculated for the evaluation of a new data compression technique using a sample radiograph. This example illustrates that a compression ratio of 1.72 can be achieved through the use of morphological skeleton representation. Two new algorithms, boundary-constrained skeleton minimization and boundary-constrained skeleton reconstruction, are also presented for improving the performance of the morphological-based coding scheme. >
['Tun-Wen Pai', 'John H. L. Hansen']
I am writing a research paper on a idea Morphological skeletonization for medical image compression
[{"from": "human", "value": "I am writing a research paper on a idea Morphological skeletonization for medical image compression"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The authors introduce a lossless data compression technique based on the morphological skeleton representation. Mathematical morphology is a methodology for image analysis which provides a means for describing the geometrical structure of an image quantitatively. A morphological skeleton representation is a useful means of illustrating the geometrical properties of an image (such as shape, size, and orientations). Since it is capable of extracting the minimum underlying geometry of an image, it can also reduce the entropy of an image (data compression). In the present work, the compression ratio is calculated for the evaluation of a new data compression technique using a sample radiograph. This example illustrates that a compression ratio of 1.72 can be achieved through the use of morphological skeleton representation. Two new algorithms, boundary-constrained skeleton minimization and boundary-constrained skeleton reconstruction, are also presented for improving the performance of the morphological-based coding scheme. >"}]