Abstract
ABSTRACTMedical images are known for their huge volume which becomes a real problem for their archiving or transmission notably for telemedicine applications. In this context, we present a new method for medical image compression which combines image definition resizing and JPEG compression. We baptise this new protocol REPro.JPEG (reduction/expansion protocol combined with JPEG compression). At first, the image is reduced then compressed before its archiving or transmission. At last, the user or the receiver decompresses the image then enlarges it before its display. The obtain results prove that, at the same number of bits per pixel lower than 0.42, that REPRo.JPEG guarantees a better preservation of image quality compared to the JPEG compression for dermatological medical images. Besides, applying the REPRo.JPEG on these colour medical images is more efficient while using the HSV colour space compared to the use of RGB or YCbCr colour spaces.
Highlights
Information is of paramount importance in our daily life and work
We present a new protocol of image compression for transmitting and archiving images based on image reduction, JPEG compression of images during storage or transmission, and decompression flowed expansion at the reception and the display
To highlight the contribution of our compression approach REPro.JPEG, we will compare its performances with those of the JPEG in terms of number of bits per pixel (NBpP) and in terms of preserving the image content quantified by PSNR and SSIM
Summary
Information is of paramount importance in our daily life and work. Information can take many forms i.e., text, signal, image and video [1]. We will focus on image type of the data These images are very rich in information which explains their large file volume [2]. The image storage requires a large space and can generate a transmission delay of the network [3]. The use of images is very common in our daily lives mainly in social networks and platforms for collaborative work [4]. In this context, image is a key component in medical diagnosis and notably in telemedicine applications [5]. Image compression is seen as the ideal solution to minimise the storage space of these images and to reduce their transmission time between different hospitals involved in a collaborative platform for telemedicine while taking into account the preservation of visual image content [6]
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