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Digital photo stitching software program is the workhorse of your panorama-making process, and may vary from providing a fully automatic one-click stitching, to some much more time-consuming manual process. This is certainly part 2 from the tutorial, which assumes all individual photos have been properly captured (stage 1 below is finished); for stage 1 and an introduction to the complete stitching process kindly visit part 1 on this tutorial on digital panoramas.

In order to begin processing our number of photos, we should select a proper software program. The greatest distinction between options is at the direction they elect to address the tradeoff between automation and suppleness. In most cases, fully customized stitching software will always achieve higher quality than automated packages, but it can possibly result in being overly technical or time consuming.

This tutorial aims to further improve comprehension of most software stitching concepts by maintaining the discussion as generic as you possibly can, however actual software features may refer to a software program called PTAssembler or PTGui (front-end for PanoTools or PTMender). PTAssembler boasts a fully-automated one-click stitching option, along with providing for almost all possible custom stitching available options in other programs.

In the course of this short article, other notable programs include the ones that come packaged together with the camera, like Canon PhotoStitch, or popular commercial packages for example Autostitch, photo printing software free, Arc Soft Panorama Maker, Panorama Factory and PanaVue, and others.


Panorama stitching software uses pairs of control points to specify areas of two camera photos that talk about a similar part of space. Pairs of control points could be manually selected by visual inspection, or this can be generated automatically using sophisticated matching algorithms (including Autopano for PTAssembler). With many photographs, greatest results are only able to be accomplished with manual control point selection (which is usually the most time-consuming stage of your software stitching process).

The example above shows a wide range of four pairs of control points, for 2 photos in a panorama. The very best control points are those which can be dependant on highly rigid objects with sharp edges or fine detail, and are spaced evenly and broadly across each overlap region (with 3-5 points for each overlap). This means that basing control points on tree limbs, clouds or water is ill-advised except when absolutely necessary. It really is that is why recommended to continually capture some land (or some other rigid objects) inside the overlap region between all pairs of photographs, otherwise control point selection may prove difficult and inaccurate (for example for panoramas containing all sky or water).

The example below demonstrates an issue in which the only detailed, rigid portion of each image is within the silhouette of land in the very bottom-thereby making it difficult to space the control points evenly across each photo’s overlap region. In these situations automated control point selection may prove better.

PTAssembler features a feature called “automatically micro-position control points,” which functions by making use of your selection as an initial guess, then looking to all adjacent pixels inside a specified distance (such as 5 pixels) to find out if these are typically a much better match. When stitching difficult cloud scenes including that shown above, this effectively combines the main advantages of manual control point selection with those of automated algorithms.

Another consideration is the way far awayfrom the digital camera each control point is physically located. For panoramas taken without having a panoramic head, parallax error can get large in foreground objects, therefore more accurate results is possible by only basing these on distant objects. Any parallax error inside the near foreground may not be visible if all these foreground elements are not contained in the overlap between photos.


Most photo stitching software gives the capability to specify where reference or vanishing reason for perspective is located, combined with the type of image projection.

Careful choice of this vanishing point can help avoid converging vertical lines (which will otherwise run parallel), or even a curved horizon. The vanishing point is usually where one could be directly facing once they were standing inside the panoramic scene. For architectural stitches, such as the example below (120° crop in the rectilinear projection), this aspect is additionally clearly apparent by using lines in the distance which are parallel to one’s line of site.

Incorrect placement from the vanishing point causes lines laying in the planes perpendicular for the viewer’s line of site to converge (though these would certainly appear for being parallel). This effect can also be observed simply by using a wide angle lens inside an architectural photo and pointing your camera significantly above or below the horizon- thereby giving the sense of buildings that are leaning.

The vanishing point is also critical in very wide angle, cylindrical projection panoramas (for example the 360 degree image shown below). It might exhibit different looking distortion if misplaced, creating a curved horizon.

When the vanishing point were placed excessive, the horizon curvature could be within the opposite direction. Sometimes it may be tough to locate the specific horizon, due to the presence of hills, mountains, trees or any other obstructions. For such difficult scenarios the positioning of the horizon could then be inferred by placing it at a height which minimizes any curvature.

Panorama stitching software also often affords the method to tilt the imaginary horizon. This can be very useful as soon as the photo containing the vanishing point was not taken perfectly level. With this scenario, whether or not the vanishing point is placed at the correct height, the horizon can be rendered as getting an S-curve in the event the imaginary horizon will not align with all the actual horizon (inside the individual photo).

In case the panorama itself were taken level, then a straightest horizon will be the one which yields a stitched image whose vertical dimension may be the shortest (and it is a technique sometimes utilized by stitching software).


Once the control points, vanishing point perspective and image projection have been chosen, the photo stitching software can then start to distort and align each image to produce the ultimate stitched photograph. This is often by far the most computationally intensive step along the way. It operates by systematically searching through mixtures of yaw, pitch and roll to be able to minimize the aggregate error between all pairs of control points. This process can also adjust lens distortion parameters, if unknown.

Keep in mind that the above mentioned photos are slightly distorted; this is to emphasize that if the stitching software positions each image it adjusts for perspective, and this the level of perspective distortion depends on that image’s location relative to the vanishing point.

The true secret quality metric to be aware of is the average distance between control points. If this type of distance is big in accordance with the print size, then seams could be visible irrespective of how well they are blended. One thing to check is if any control points were mistakenly placed, and they stick to the other guidelines placed in stage 2. In the event the average distance remains too big then this can be brought on by improperly captured images, including parallax error from camera movement or not by using a panoramic head.


Ideally one would like to place the photo seams along unimportant or natural break points within the scene. When the stitching software supports layered output one could perform this manually by using a mask in photoshop:

Without Blend Manual Blend Mask from Manual Blend

Note how the above manual blend evens the skies and avoids visible jumps along geometrically prominent architectural lines, including the crescent of pillars, foreground row of statues and distant white building.

Make sure to blend the mask over large distances for smooth textures, like the sky region above. For fine detail, blending over large distances can blur the image if you have any misalignment between photos. It is therefore wise to blend fine details over short distances using seams which avoid any easily noticeable discontinuities (see the “mask from manual blend” above to find out the way the sky and buildings were blended).

On the flip side, manually blending seams can be extremely time-consuming. Fortunately hd photography software free download comes with an automated feature which may perform this simultaneously, as described in the following section.


Among the finest methods to blend seams inside a stitched photograph is to utilize an approach called “multi-resolution splines”, that may often rectify even poorly captured panoramas or mosaics. It operates by breaking each image up into several components, comparable to how an RGB photo can be separated into individual red, green and blue channels, although in such a case each component represents another scale of image texture. Small-scale features (including foliage or fine grass) have a superior spatial resolution, whereas larger scale features (for instance a clear sky gradient) have been proved to obtain low spatial resolutions.