Certain group of snakes do what no other animal or artificial device can do.They form detailed image of extremely small heat signatures,what is most fascinating is that they do this with receptor that are microscopic in size,extraordinarily sensitive,uncooled and are able to repair themselves.
Snakes infra-red imagers are at least 10 times more sensitive than the best artificial infra-red sensor
HOW DOES THE SNAKE See ?
The detection system consist of cavities located on each side of head called pit organs,operated on principle similar to that of pinhole camera.Pit viper and boids the tow snake that possess this ability,have heat -sensitive membranes that can detect the difference in temperature between a moving prey and its surrounding on scale of mK.IF the radiation intensity hitting the membrane itself,membrane heats up that location.The picture of such cavities is presented in fig below.
.b) A pit vipers infra-red sensitive pit organ works like a pinhole camera.
According to the Planck radiation law as an approximation of the emitted heat intensity,99% of the radiation is emitted at wavelengths under 75 micrometers and the radiation intensity is maximal at 9.5 micrometers which is within the 8-12 micrometers IR atmospheric transmittance window.
Because the pit hole is very large compared to the membrane size,the radiation strikes many points.Optical quality of the infra-res vision is much too blurry to allow snakes to strike prey with the observed accuracy of about 5 degrees.The most fascinating is an amount of heat-sensitive sensors and their precision.
In Pit vipers,which have only two pit holes ( One in front of each eye ), a block of about 1600 sensory cells lie on membrane which has field of view of about 100 degree.This means the snake's brain would receive an image resolution of about 2.5 degrees for point -like objects,such as eyes,which are one of the hottest points on mammals.
If the aperture was very small,the amount of energy per unit time (second) reaching the membrane would also be small.The need together a reasonable amount of thermal energy per second necessitates the " Pin Hole " of the pit organ to be very large,thus greatly reducing its optical performance.If on the other to be very large,thus greatly reducing its optical performance .If on the other hand the aperture of the organ is large,the image of a point source of heat is disc-shaped rather than point-like.
Since ,however ,the size of disc-shaped image may be determined by the detectors on the membrane,it is still possible to tell from which direction the radiation comes ,ensuring directional sensitivity of the system. The aperture size was probably an evolutionary trade off between image sharpness and radiant flux.Although image that us formed of the pit membrane ha very low quality the information that is needed to reconstruct the original temperature distribution in space is still available.
So how a snake could possible use such poorly focused IR input to find its prey in darkness with a surprising angular precision of 5 degrees ?How the snake may be able to extract information on the location of the prey from the blurred image that is formed on the Pit-membrane.
WHAT DOES THE SNAKE SEE ?
Without the ability of real time imaging the IR organ would be of little use for the snake.so Dr.Van Hemmen proved that it is possible to reconstruct the original heat distribution using the blurred image on the membrane.
The image on the membrane resulting from the total heat distribution in space will be some complicated shape that consist of the superposition of the contribution of all heat sources.A superposition of edge detector in the brain can now reconstruct the heat distribution by using the whole image on the membrane for each point in space to be reconstructed so reconstruction is possible because the information is still available in th blurred image on the pit membrane,where the receptor are. As a demonstration of the model image was used
Figure -2: The Famous hare by Durer ( left ) was coverted into 8-bit gray at a resolution of 32X32 (right).
Since a snake has limited computational resources ( all " Calculations"must be realizable in neuronal ' 'Hardware ' ') the reconstruction model must be simple.Our Model thus uses only one computational step ( it is non iterative) to estimate the input image from the measured response on the pit membrane.It resembles a wiener filter and is akin to,but different from,some of the algorithms used in image reconstruction.
So it is highly remarkable that snakes can perform some kind of an image processing like our artificial devices based on " wave front coding" and ' ' Pupil engineering techniques.
IMAGE PROCESSING IN NATURE
There was developed a neuronal algorithm that accurately reconstructed the heat image from the membrane.The Most vital requirements is accurate detectors and the ability to detect edges in the images produced on the pit membrane,.That is similar to the situation with " wave front coding " device :The dynamic range and accuracy of the ADC is much more important that it is much more important than an amount of elements.
I would like to introduce an analogy here: such imaging like drawing a picture on a sand.The more fine the sand ,the more accurate and delicate pictures one can draw.That is the case of high dynamic range of the detector.And vice cersa: on a coarse and stony sand it is difficult to draw a fine tracery that is the case of low dynamic ranges detector.
But let us get back to the model of snake vision:
The model has a fairly high noise tolerance.For input noise levels up to 50%,the hare is recognizable Sensitivity to measurement errors corresponds to about 3 degrees.For detector noise levels up to about 1% of the membrane heat intensity,a good reconstruction is about one pixel accuracy.At detector noise levels beyond about 1% of the membrane heat intensity, a good reconstruction is about one pixel accuracy .At detector noise levels beyond about 1% the image is not so easily recognizable,but the presence of an object is still evident.
The assumptions that went into the calculations are a "worst case scenario".For instance,we assumed that the input to the pit organ is totally uncorrelated, meaning that the snake has no idea what heat distribution to expect.In reality,important information about the environment is always available.For example,typical temperature and size of aprey animal may be encoded in th neuronal processing structure.If the snake " know"what kind of images to expect,the reconstruction process can be enhanced considerably.
Since ,however ,the size of disc-shaped image may be determined by the detectors on the membrane,it is still possible to tell from which direction the radiation comes ,ensuring directional sensitivity of the system. The aperture size was probably an evolutionary trade off between image sharpness and radiant flux.Although image that us formed of the pit membrane ha very low quality the information that is needed to reconstruct the original temperature distribution in space is still available.
So how a snake could possible use such poorly focused IR input to find its prey in darkness with a surprising angular precision of 5 degrees ?How the snake may be able to extract information on the location of the prey from the blurred image that is formed on the Pit-membrane.
WHAT DOES THE SNAKE SEE ?
Without the ability of real time imaging the IR organ would be of little use for the snake.so Dr.Van Hemmen proved that it is possible to reconstruct the original heat distribution using the blurred image on the membrane.
The image on the membrane resulting from the total heat distribution in space will be some complicated shape that consist of the superposition of the contribution of all heat sources.A superposition of edge detector in the brain can now reconstruct the heat distribution by using the whole image on the membrane for each point in space to be reconstructed so reconstruction is possible because the information is still available in th blurred image on the pit membrane,where the receptor are. As a demonstration of the model image was used
Figure -2: The Famous hare by Durer ( left ) was coverted into 8-bit gray at a resolution of 32X32 (right).
Since a snake has limited computational resources ( all " Calculations"must be realizable in neuronal ' 'Hardware ' ') the reconstruction model must be simple.Our Model thus uses only one computational step ( it is non iterative) to estimate the input image from the measured response on the pit membrane.It resembles a wiener filter and is akin to,but different from,some of the algorithms used in image reconstruction.
So it is highly remarkable that snakes can perform some kind of an image processing like our artificial devices based on " wave front coding" and ' ' Pupil engineering techniques.
IMAGE PROCESSING IN NATURE
There was developed a neuronal algorithm that accurately reconstructed the heat image from the membrane.The Most vital requirements is accurate detectors and the ability to detect edges in the images produced on the pit membrane,.That is similar to the situation with " wave front coding " device :The dynamic range and accuracy of the ADC is much more important that it is much more important than an amount of elements.
I would like to introduce an analogy here: such imaging like drawing a picture on a sand.The more fine the sand ,the more accurate and delicate pictures one can draw.That is the case of high dynamic range of the detector.And vice cersa: on a coarse and stony sand it is difficult to draw a fine tracery that is the case of low dynamic ranges detector.
But let us get back to the model of snake vision:
The model has a fairly high noise tolerance.For input noise levels up to 50%,the hare is recognizable Sensitivity to measurement errors corresponds to about 3 degrees.For detector noise levels up to about 1% of the membrane heat intensity,a good reconstruction is about one pixel accuracy.At detector noise levels beyond about 1% of the membrane heat intensity, a good reconstruction is about one pixel accuracy .At detector noise levels beyond about 1% the image is not so easily recognizable,but the presence of an object is still evident.
The assumptions that went into the calculations are a "worst case scenario".For instance,we assumed that the input to the pit organ is totally uncorrelated, meaning that the snake has no idea what heat distribution to expect.In reality,important information about the environment is always available.For example,typical temperature and size of aprey animal may be encoded in th neuronal processing structure.If the snake " know"what kind of images to expect,the reconstruction process can be enhanced considerably.
How does the reconstruction matrix become imprinted on the snake's neural circuitry in the first place? ``It can't be genetic coding,'' says van Hemmen. ``The snake would need a suitcase full of genes to encode such detail. Besides we know that snakes ...need a season of actual learning, not just anatomical maturation, to acquire their extraordinary skills.''... [11]
On the Fig. 3 it is shown a deconvolution results that give us a concept of the snakes vision capabilities.
Figure 3: On the left, this figure displays the membrane heat intensity as captured by the ``pithole camera''. On the right are reconstructions for four different membrane noise levels. The pit membrane was taken as a flat square containing41x41 receptors. The model works equally well if applied to other membrane shapes. The membrane noise term was taken to be Gaussian with SIGMA= 25, 100, 200, and 500 from left to right and top to bottom, corresponding to 0.25%, 1%, 2%, and 5% of the maximal membrane intensity. The image from the paper [2]
Ultimately, a snake's ability to utilize information from the pit organs depends on its capability to detect edges in the image produced on the pit membrane. If the snake performed no reconstruction, but instead simply targeted bloblike ``hot spots'' on the membrane, it would still have to be able to discern the edge of the blob. The present model performs edge detection for all spatial positions and hence automatically creates a full reconstruction. A level of neuronal processing beyond what is represented in our model is unlikely to be beneficial since the quality of the system is fundamentally limited by the relatively small number of heat receptors.[5]