Since the two projectors cannot occupy exactly the same space, the output of each must be at least slightly corrected for Keystone Distortion. In this application, two or more projectors are projected onto exactly the same surface. Projector Stacking is an advanced form of keystone correction. For more complex distortion correction, an external processor is required. Keystone correction is ideal for simple business (i.e. Even with this feature, the degree of adjustment available is limited, and image quality may suffer. Keystone correction capabilities are now included in most projectors currently available on the market, allowing users to move the image both vertically and horizontally. Keystone distortion gets its name from the symmetric trapezoidal distortion resulting from misaligned projector placement in the vertical dimension (although the term is generally applied to the non-symmetric quadrilateral shape that occurs from an off-axis projection in both dimensions). The simplest application of image geometry correction is a specific case known as keystone distortion correction derived from Keystone effect. In the case of Keystone Correction, 4 points are all that are required to completely describe any projection situation. The number of points in the 2-dimensional array that are required to do an accurate Image Geometry Correction depends on the surface involved. In all methods, the transformation is generally described as a 2-dimensional array. a camera can be used to evaluate the alignment of test images), or by user iteration (i.e. calculating exactly where an image should land on a regular surface such as sphere or a cylinder), or by an automatic optical feedback system (i.e. The image geometry correction transformation can be calculated by predictive geometry (i.e. This extra expense can be mitigated by the inclusion of additional features (such as switching and Edge Blending in the Signal Processing based image geometry correction system).Ĭalculation of the image geometry correction transformation The drawback of Signal Processing based Image Geometry Correction is the extra expense of the hardware that is used to perform it. Signal Processing based image geometry correction is the most flexible form of this technology, enabling the correction of images that originate from ANY graphics controller platform. IDT, Silicon Optix or GEO Semiconductor), or in stand-alone Video Signal Processors (i.e. Signal Processing based image geometry correction is implemented by specially designed hardware in the projection system (i.e. Special care must be taken in the design of the scaling filter to ensure that spatial frequencies remain balanced in all areas of the image, and that the Nyquist criterion is met in all areas of the image. The scaling operation is performed with different scaling ratios in different parts of the image, according to the defined transformation. In Signal Processing based image geometry correction, the spatial transformation consists of spatially defined 2-dimensional image re-sampling or scaling filter. Its major drawback is that it is tied to the graphics controller platform, and cannot process signals that originate outside the graphics controller. Graphics Processing based image geometry correction is very effective for content that originates in the PC. Mersive Technologies and Scalable Display Technologies).
#EDGE BLENDING ON CURVED WALL SOFTWARE#
The sophisticated software that uses the texture mapping hardware of a graphics controller is not standard, and is available only through vendors of specialty software (i.e. Graphics Processing based Image Geometry Correction, may be performed with inexpensive PC-based graphics controllers. Each polygon on the input image is thus applied to an equivalent (but transformed in shape and location) polygon in the output image. The transformation is executed by texture mapping from the rectilinear mesh of the input image to the transformed shape of the destination image. In Graphics Processing, the spatial transformation consists of a polygon mesh (usually triangles). The spatial transformation must be pre-defined for a particular desired geometric, and may be calculated by several different methods (more to follow). Image geometry correction is generally implemented in 2 different ways:īoth techniques involve the real time execution of a spatial transformation from the input image to the output image, and both techniques require powerful hardware.
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