Study of Surgery Stereo Image Compression
Ravipas Ounsuwan 1, and Kazuhiko Hamamoto 2
11

Graduate School of Engineering, Course of Information and Engineering, Tokai University, Japan
2
School of Information and Telecommunication Engineering, Tokai University, Japan

Introduction

Surgery System is applied not only in term of the Medical
usage but also Education. Nowadays, this system can be sent toother places in real-time. In order to, maintain the resolution on
both images, the system needs to increase the amountinformation for double. In this case, the transmission speed willdrop. Therefore, the Study of Surgery Stereo Image
Compression becomes necessary.

are mixtures of these three colors. And the amount of color
humans see also depends on the strength, concentration, andposition of the light source. [2]In the research, as we are working on Surgery Stereo
Image, therefore, we have considered that this method mightwork not only the Natural Stereo Image but also the Surgery
Image.

23

Research and Proposed Methods

Stereo Image is the pair of images, which are taken from thedifferent perspective views. There are two types of stereo image:
Parallel type and Toe-in type.
- The Parallel type is the pair of images, which are taken byaligning two cameras in parallel or use only one camera andshift the camera in parallel direction.
- Toe-in type is the pair of images, which are taken byrotating two cameras for making an angle. And these twocameras need to point at the same object(s).
In this research, we have focused on surgery stereo images,
which are taken in Toe-in type. In term of compression, we havefocused on both lossless and lossy compression. Therefore, we’dto divide our proposed method into two methods: Disparity
method, which based on lossless compression and Color:Graymethod, which based on lossy compression.
Disparity Method
This method is based on lossless compression. The goal is totransform the Toe-in Stereo Image back to Parallel Stereo Imageby using the Block Matching and Optical Flow’s Vector
Calculation. And after we could transform the image In Parallel
type, the camera(s) is aligned in parallel direction, which means
the differences on both images are relied on shift value. And that
seems easier to find the disparity value than Toe-in type.
Because of the angle between camera and objects make thedirection of Optical Flow’s vectors become unpredictable,
which means the calculation also difficult.

Experiment and Result

3.1

Disparity Method
In this method, we have used the Toe-in type of stereo
image along with the Block Matching Algorithm. However, it isdifficult to find the shift value due to the problem of angle inToe-in stereo image. In the experiment, we have simulated the3D environment of Toe-in Stereo Image by using OpenGL andOptical Flow’s Vector by using OpenCV [3, 4] as shown infigures below:

2.1

2.2

Color:Gray Method
This method is based on lossless compression. This methodof requiring only one color image, which means when we view
the stereo pair, we just need only one color image and one grayimage. In this case, we can reduce the size of stereo image. By
the way, when we use the gray image instead of color image, weneed to concern about these two important factors: Human
Depth Perception and Human Color Perception.
- Human Depth Perception is the human’s visual ability toperceive the world in three dimensions (3D) and the distance ofan object [1]- Human Color Perception is the human’s visual ability toperceive the presence of light sensitive cells in the eyes called
rod and cone. But the research has shown that the rods do notseem to be involved in the perception of color in human beings.
There are three types of cones in retina. Each type of cone
detects either red, green, or blue. All other colors humans see

Fig. 1. Simulation of Stereo Image: Toe-in (Left), Stereo
Image with Optical Flow’s Vector (Right)
According to the Optical Flow’s figure above, there aremany lines of vectors, diagonal and horizontal. As we can seethat the vectors are mostly found at the corner of the objects
because the optical flow is difficult to apply on texture of anobject. Normally, in optical flow, the more vectors come closer
to the center, the more shortened vectors will become, whichmean there is no movement at the center of an object. Therefore,
when we calculate the length of the vector, we need to select thevector that sticks to the corner like the blue circle’s positions
that shown in figure 1.
After that, we also applied the Optical Flow to the Surgery
Stereo Image as shown in a figure below:

Fig. 2. Surgery Stereo Image (Toe-in) with Optical Flow’sVector
In Surgery Stereo Image, it differs from the Simulated
Stereo Image because it contains textures with brightness, whichbecomes the important factors when we want to calculate theshift value from the vector. According to vectors in figure 2,
which are spread in and out from the objects unlike in thesimulation one. However, we need to focus on the vector at thecorner of the objects. After that, we might understand thevector’s directions and transform it back to parallel type for thepurpose of compression.
3.2Color:Gray Method
The method of Color:Gray is based on one of the research
paper [5]. And we have applied this method to our research andset up the experiment. In the experiment, we have used thequestionnaire as the evaluation method.

Fig. 5. Human Color Perception’s Result

Fig. 3. Color:Gray Method’s Experiment
Questionnaire’s Details:- The evaluation of Human Depth Perception for ten levels(level 1 means the subject cannot feel any depth from the stereo
image and level 10 means the subject can feel the depth from thestereo image clearly).
- The evaluation of Human Color Perception for ten levels(level 1 means the subject see only grayscale from the stereo
image level 10 means the subject can see the color from thestereo image as clear as the original stereo image).
Experiment’s Details:- We have prepared the 4 sets of stereo images: 3 sets ofSurgery Stereo Image and 1 set of Natural Stereo Image. And ineach set we also have divided the stereo image pairs into 4 pairs:“Left:Color Right:Color pair”, “Left:Color Right:Gray pair”,“Left:Gray Right:Color pair”, and “Left:Gray Right:Gray pair”.
- In the experiment, we have used the shutter glasses as astereo image viewer.
- During the experiment, after the subject saw the stereo pairs
in each set, he/she will be asked to answer some couple
questions like “Did you feel any depth in the image?” for theevaluation of Human Depth Perception and “Did you see thecolor in the image clearly? ” for the evaluation of Human Color
Perception. The answers will be evaluated by score from 1 to 10.
3.2.2 Experiment’s Results- Test Subjects: 16 persons (Male: 13 persons, Female 3persons)According to Human Depth Perception graph, when we havecompared the Color:Color pair(Original) to Color:Gray pair, andwe have found that the results are not so different, especially,
between Surgery Stereo Image and Natural Stereo Image.
In Human Color Perception graph, we also have compared
the Color:Color pair(Original) to Color:Gray pair, and we havefound that the subject can see the color clearer in theColor:Color pair. And the Natural Image’s results seem to bebetter than the Surgery Stereo Image.
4Conclusion

In this research, we have considered both losslesscompression and lossy compression. Therefore, in this research
we have two proposed methods, which are Disparity Method
and Color:Gray Method.
- Disparity Image method uses the block matching algorithmwith Optical Flow’s Vector to find the shift value. In theexperiment, we have simulated the 3D environment with some
objects and camera’s viewpoints. And we also have tested on
the original stereo image. Unfortunately, due to the angle
problem, this method is still not yet completed.
- Color:Gray method uses the grayscale image to reduce theinformation of stereo image. According to the experiment, I
found that Color:Gray pair might be able to use for compressionin term of color perception.
In the future, we have planned to continue the Disparity
Image method by calculating the vector values and directions totransform the Toe-in stereo image back to parallel stereo image.
And for Color:Gray method, as our research is based on theSurgery Image, and we have found that the components of RGBin Surgery Image, red channel seems to be the most effective
color such as the color of blood or the color of human’sinternal organs. Therefore, we have planned to use its
characteristics to improve the gray image for the experiment tomake it as close as possible to the original Color:Color pair.
Lastly, the results must be evaluated by doctors.
References
[1]
[2]
[3]
[4]
[5]

Fig. 4. Human Depth Perception’s Result[6]

Wikipedia, “Depth Perception", Last modified 11 May 2012,
http://en.wikipedia.org/wiki/Depth_perception
MSDN, “Human Color Perception", 16 November 2010,
http://msdn.microsoft.com/en-us/library/dd372109(v=vs.85).aspx
OpenCVプログラミングブック第２版、奈良先端科学技術大学院大学、“テンプレートマッチイング”、p.206
内村圭一・上瀧 剛、実践画像処理入門、“ブロックマッチングによる差分画像の生成”、p.151
Yael Termin, Gal A. Kaminka, “Color stereoscopic images
requiring only one color image", Optical Eng. Vol.46, No.8,
pp.087003-1-11 (August 2007)
Udo Ahlvers, Udo Zoelzer, Gerd Heinrich, “Efficient Adaptive
Lossless Stereo Image Coding", IWSSIP'04: international
workshop on systems, signals and image processing, Poznan ,POLOGNE, pp. 267-270, 2004